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Repository: karpathy/minbpe
Branch: master
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Directory structure:
gitextract_st7_oioa/
├── .gitignore
├── LICENSE
├── README.md
├── exercise.md
├── lecture.md
├── minbpe/
│ ├── __init__.py
│ ├── base.py
│ ├── basic.py
│ ├── gpt4.py
│ └── regex.py
├── requirements.txt
├── tests/
│ ├── __init__.py
│ ├── taylorswift.txt
│ └── test_tokenizer.py
└── train.py
================================================
FILE CONTENTS
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FILE: .gitignore
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__pycache__/
.DS_Store
models/**/*
*.pytest_cache
*.model
*.vocab
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FILE: LICENSE
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MIT License
Copyright (c) 2024 Andrej
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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The above copyright notice and this permission notice shall be included in all
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: README.md
================================================
# minbpe
Minimal, clean code for the (byte-level) Byte Pair Encoding (BPE) algorithm commonly used in LLM tokenization. The BPE algorithm is "byte-level" because it runs on UTF-8 encoded strings.
This algorithm was popularized for LLMs by the [GPT-2 paper](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf) and the associated GPT-2 [code release](https://github.com/openai/gpt-2) from OpenAI. [Sennrich et al. 2015](https://arxiv.org/abs/1508.07909) is cited as the original reference for the use of BPE in NLP applications. Today, all modern LLMs (e.g. GPT, Llama, Mistral) use this algorithm to train their tokenizers.
There are two Tokenizers in this repository, both of which can perform the 3 primary functions of a Tokenizer: 1) train the tokenizer vocabulary and merges on a given text, 2) encode from text to tokens, 3) decode from tokens to text. The files of the repo are as follows:
1. [minbpe/base.py](minbpe/base.py): Implements the `Tokenizer` class, which is the base class. It contains the `train`, `encode`, and `decode` stubs, save/load functionality, and there are also a few common utility functions. This class is not meant to be used directly, but rather to be inherited from.
2. [minbpe/basic.py](minbpe/basic.py): Implements the `BasicTokenizer`, the simplest implementation of the BPE algorithm that runs directly on text.
3. [minbpe/regex.py](minbpe/regex.py): Implements the `RegexTokenizer` that further splits the input text by a regex pattern, which is a preprocessing stage that splits up the input text by categories (think: letters, numbers, punctuation) before tokenization. This ensures that no merges will happen across category boundaries. This was introduced in the GPT-2 paper and continues to be in use as of GPT-4. This class also handles special tokens, if any.
4. [minbpe/gpt4.py](minbpe/gpt4.py): Implements the `GPT4Tokenizer`. This class is a light wrapper around the `RegexTokenizer` (2, above) that exactly reproduces the tokenization of GPT-4 in the [tiktoken](https://github.com/openai/tiktoken) library. The wrapping handles some details around recovering the exact merges in the tokenizer, and the handling of some unfortunate (and likely historical?) 1-byte token permutations.
Finally, the script [train.py](train.py) trains the two major tokenizers on the input text [tests/taylorswift.txt](tests/taylorswift.txt) (this is the Wikipedia entry for her kek) and saves the vocab to disk for visualization. This script runs in about 25 seconds on my (M1) MacBook.
All of the files above are very short and thoroughly commented, and also contain a usage example on the bottom of the file.
## quick start
As the simplest example, we can reproduce the [Wikipedia article on BPE](https://en.wikipedia.org/wiki/Byte_pair_encoding) as follows:
```python
from minbpe import BasicTokenizer
tokenizer = BasicTokenizer()
text = "aaabdaaabac"
tokenizer.train(text, 256 + 3) # 256 are the byte tokens, then do 3 merges
print(tokenizer.encode(text))
# [258, 100, 258, 97, 99]
print(tokenizer.decode([258, 100, 258, 97, 99]))
# aaabdaaabac
tokenizer.save("toy")
# writes two files: toy.model (for loading) and toy.vocab (for viewing)
```
According to Wikipedia, running bpe on the input string: "aaabdaaabac" for 3 merges results in the string: "XdXac" where X=ZY, Y=ab, and Z=aa. The tricky thing to note is that minbpe always allocates the 256 individual bytes as tokens, and then merges bytes as needed from there. So for us a=97, b=98, c=99, d=100 (their [ASCII](https://www.asciitable.com) values). Then when (a,a) is merged to Z, Z will become 256. Likewise Y will become 257 and X 258. So we start with the 256 bytes, and do 3 merges to get to the result above, with the expected output of [258, 100, 258, 97, 99].
## inference: GPT-4 comparison
We can verify that the `RegexTokenizer` has feature parity with the GPT-4 tokenizer from [tiktoken](https://github.com/openai/tiktoken) as follows:
```python
text = "hello123!!!? (안녕하세요!) 😉"
# tiktoken
import tiktoken
enc = tiktoken.get_encoding("cl100k_base")
print(enc.encode(text))
# [15339, 4513, 12340, 30, 320, 31495, 230, 75265, 243, 92245, 16715, 57037]
# ours
from minbpe import GPT4Tokenizer
tokenizer = GPT4Tokenizer()
print(tokenizer.encode(text))
# [15339, 4513, 12340, 30, 320, 31495, 230, 75265, 243, 92245, 16715, 57037]
```
(you'll have to `pip install tiktoken` to run). Under the hood, the `GPT4Tokenizer` is just a light wrapper around `RegexTokenizer`, passing in the merges and the special tokens of GPT-4. We can also ensure the special tokens are handled correctly:
```python
text = "<|endoftext|>hello world"
# tiktoken
import tiktoken
enc = tiktoken.get_encoding("cl100k_base")
print(enc.encode(text, allowed_special="all"))
# [100257, 15339, 1917]
# ours
from minbpe import GPT4Tokenizer
tokenizer = GPT4Tokenizer()
print(tokenizer.encode(text, allowed_special="all"))
# [100257, 15339, 1917]
```
Note that just like tiktoken, we have to explicitly declare our intent to use and parse special tokens in the call to encode. Otherwise this can become a major footgun, unintentionally tokenizing attacker-controlled data (e.g. user prompts) with special tokens. The `allowed_special` parameter can be set to "all", "none", or a list of special tokens to allow.
## training
Unlike tiktoken, this code allows you to train your own tokenizer. In principle and to my knowledge, if you train the `RegexTokenizer` on a large dataset with a vocabulary size of 100K, you would reproduce the GPT-4 tokenizer.
There are two paths you can follow. First, you can decide that you don't want the complexity of splitting and preprocessing text with regex patterns, and you also don't care for special tokens. In that case, reach for the `BasicTokenizer`. You can train it, and then encode and decode for example as follows:
```python
from minbpe import BasicTokenizer
tokenizer = BasicTokenizer()
tokenizer.train(very_long_training_string, vocab_size=4096)
tokenizer.encode("hello world") # string -> tokens
tokenizer.decode([1000, 2000, 3000]) # tokens -> string
tokenizer.save("mymodel") # writes mymodel.model and mymodel.vocab
tokenizer.load("mymodel.model") # loads the model back, the vocab is just for vis
```
If you instead want to follow along with OpenAI did for their text tokenizer, it's a good idea to adopt their approach of using regex pattern to split the text by categories. The GPT-4 pattern is a default with the `RegexTokenizer`, so you'd simple do something like:
```python
from minbpe import RegexTokenizer
tokenizer = RegexTokenizer()
tokenizer.train(very_long_training_string, vocab_size=32768)
tokenizer.encode("hello world") # string -> tokens
tokenizer.decode([1000, 2000, 3000]) # tokens -> string
tokenizer.save("tok32k") # writes tok32k.model and tok32k.vocab
tokenizer.load("tok32k.model") # loads the model back from disk
```
Where, of course, you'd want to change around the vocabulary size depending on the size of your dataset.
**Special tokens**. Finally, you might wish to add special tokens to your tokenizer. Register these using the `register_special_tokens` function. For example if you train with vocab_size of 32768, then the first 256 tokens are raw byte tokens, the next 32768-256 are merge tokens, and after those you can add the special tokens. The last "real" merge token will have id of 32767 (vocab_size - 1), so your first special token should come right after that, with an id of exactly 32768. So:
```python
from minbpe import RegexTokenizer
tokenizer = RegexTokenizer()
tokenizer.train(very_long_training_string, vocab_size=32768)
tokenizer.register_special_tokens({"<|endoftext|>": 32768})
tokenizer.encode("<|endoftext|>hello world", allowed_special="all")
```
You can of course add more tokens after that as well, as you like. Finally, I'd like to stress that I tried hard to keep the code itself clean, readable and hackable. You should not have feel scared to read the code and understand how it works. The tests are also a nice place to look for more usage examples. That reminds me:
## tests
We use the pytest library for tests. All of them are located in the `tests/` directory. First `pip install pytest` if you haven't already, then:
```bash
$ pytest -v .
```
to run the tests. (-v is verbose, slightly prettier).
## community extensions
* [gnp/minbpe-rs](https://github.com/gnp/minbpe-rs): A Rust implementation of `minbpe` providing (near) one-to-one correspondence with the Python version
## exercise
For those trying to study BPE, here is the advised progression exercise for how you can build your own minbpe step by step. See [exercise.md](exercise.md).
## lecture
I built the code in this repository in this [YouTube video](https://www.youtube.com/watch?v=zduSFxRajkE). You can also find this lecture in text form in [lecture.md](lecture.md).
## todos
- write a more optimized Python version that could run over large files and big vocabs
- write an even more optimized C or Rust version (think through)
- rename GPT4Tokenizer to GPTTokenizer and support GPT-2/GPT-3/GPT-3.5 as well?
- write a LlamaTokenizer similar to GPT4Tokenizer (i.e. attempt sentencepiece equivalent)
## License
MIT
================================================
FILE: exercise.md
================================================
# exercise
Build your own GPT-4 Tokenizer!
### Step 1
Write the `BasicTokenizer` class, with the following three core functions:
- `def train(self, text, vocab_size, verbose=False)`
- `def encode(self, text)`
- `def decode(self, ids)`
Train your tokenizer on whatever text you like and visualize the merged tokens. Do they look reasonable? One default test you may wish to use is the text file `tests/taylorswift.txt`.
### Step 2
Convert you `BasicTokenizer` into a `RegexTokenizer`, which takes a regex pattern and splits the text exactly as GPT-4 would. Process the parts separately as before, then concatenate the results. Retrain your tokenizer and compare the results before and after. You should see that you will now have no tokens that go across categories (numbers, letters, punctuation, more than one whitespace). Use the GPT-4 pattern:
```
GPT4_SPLIT_PATTERN = r"""'(?i:[sdmt]|ll|ve|re)|[^\r\n\p{L}\p{N}]?+\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]++[\r\n]*|\s*[\r\n]|\s+(?!\S)|\s+"""
```
### Step 3
You're now ready to load the merges from the GPT-4 tokenizer and show that your tokenizer produces the identical results for both `encode` and `decode`, matching [tiktoken](https://github.com/openai/tiktoken).
```
# match this
import tiktoken
enc = tiktoken.get_encoding("cl100k_base") # this is the GPT-4 tokenizer
ids = enc.encode("hello world!!!? (안녕하세요!) lol123 😉")
text = enc.decode(ids) # get the same text back
```
Unfortunately, you will run into two issues:
1. It is not trivial to recover the raw merges from the GPT-4 tokenizer. You can easily recover what we call `vocab` here, and what they call and store under `enc._mergeable_ranks`. Feel free to copy paste the `recover_merges` function in `minbpe/gpt4.py`, which takes these ranks and returns the raw merges. If you wish to know how this function works, read [this](https://github.com/openai/tiktoken/issues/60) and [this](https://github.com/karpathy/minbpe/issues/11#issuecomment-1950805306). Basically, under some conditions it is enough to only store the parent nodes (and their rank) and get rid of the precise details of which children merged up to any parent.
2. Second, the GPT-4 tokenizer for some reason permutes its raw bytes. It stores this permutation in the first 256 elements of the mergeable ranks, so you can recover this byte shuffle relatively simply as `byte_shuffle = {i: enc._mergeable_ranks[bytes([i])] for i in range(256)}`. In both your encode and decode, you'll have to shuffle bytes around accordingly. If you're stuck, reference the minbpe/gpt4.py` file for hints.
### Step 4
(Optional, irritating, not obviously useful) Add the ability to handle special tokens. You'll then be able to match the output of tiktoken even when special tokens are present, e.g.:
```
import tiktoken
enc = tiktoken.get_encoding("cl100k_base") # this is the GPT-4 tokenizer
ids = enc.encode("<|endoftext|>hello world", allowed_special="all")
```
Without `allowed_special` tiktoken will error.
### Step 5
If you've made it this far, you're now a pro at LLM Tokenization! Sadly, you're not exactly done yet because a lot of LLMs outside of OpenAI (e.g. Llama, Mistral) use [sentencepiece](https://github.com/google/sentencepiece) instead. Primary difference being that sentencepiece runs BPE directly on Unicode code points instead of on UTF-8 encoded bytes. Feel free to explore sentencepiece on your own (good luck, it's not too pretty), and stretch goal if you really experience and suffer from the burden of time, re-write your BPE to be on Unicode code points and match the Llama 2 tokenizer.
================================================
FILE: lecture.md
================================================
# LLM Tokenization
Hi everyone, today we are going to look at Tokenization in Large Language Models (LLMs). Sadly, tokenization is a relatively complex and gnarly component of the state of the art LLMs, but it is necessary to understand in some detail because a lot of the shortcomings of LLMs that may be attributed to the neural network or otherwise appear mysterious actually trace back to tokenization.
### Previously: character-level tokenization
So what is tokenization? Well it turns out that in our previous video, [Let's build GPT from scratch](https://www.youtube.com/watch?v=kCc8FmEb1nY), we already covered tokenization but it was only a very simple, naive, character-level version of it. When you go to the [Google colab](https://colab.research.google.com/drive/1JMLa53HDuA-i7ZBmqV7ZnA3c_fvtXnx-?usp=sharing) for that video, you'll see that we started with our training data ([Shakespeare](https://raw.githubusercontent.com/karpathy/char-rnn/master/data/tinyshakespeare/input.txt)), which is just a large string in Python:
```
First Citizen: Before we proceed any further, hear me speak.
All: Speak, speak.
First Citizen: You are all resolved rather to die than to famish?
All: Resolved. resolved.
First Citizen: First, you know Caius Marcius is chief enemy to the people.
All: We know't, we know't.
```
But how do we feed strings into a language model? Well, we saw that we did this by first constructing a vocabulary of all the possible characters we found in the entire training set:
```python
# here are all the unique characters that occur in this text
chars = sorted(list(set(text)))
vocab_size = len(chars)
print(''.join(chars))
print(vocab_size)
# !$&',-.3:;?ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz
# 65
```
And then creating a lookup table for converting between individual characters and integers according to the vocabulary above. This lookup table was just a Python dictionary:
```python
stoi = { ch:i for i,ch in enumerate(chars) }
itos = { i:ch for i,ch in enumerate(chars) }
# encoder: take a string, output a list of integers
encode = lambda s: [stoi[c] for c in s]
# decoder: take a list of integers, output a string
decode = lambda l: ''.join([itos[i] for i in l])
print(encode("hii there"))
print(decode(encode("hii there")))
# [46, 47, 47, 1, 58, 46, 43, 56, 43]
# hii there
```
Once we've converted a string into a sequence of integers, we saw that each integer was used as an index into a 2-dimensional embedding of trainable parameters. Because we have a vocabulary size of `vocab_size=65`, this embedding table will also have 65 rows:
```python
class BigramLanguageModel(nn.Module):
def __init__(self, vocab_size):
super().__init__()
self.token_embedding_table = nn.Embedding(vocab_size, n_embd)
def forward(self, idx, targets=None):
tok_emb = self.token_embedding_table(idx) # (B,T,C)
```
Here, the integer "plucks out" a row of this embedding table and this row is the vector that represents this token. This vector then feeds into the Transformer as the input at the corresponding time step.
### "Character chunks" for tokenization using the BPE algorithm
This is all well and good for the naive setting of a character-level language model. But in practice, in state of the art language models, people use a lot more complicated schemes for constructing these token vocabularies. In particular, these schemes work not on a character level, but on character chunk level. And the way these chunk vocabularies are constructed is by using algorithms such as the **Byte Pair Encoding** (BPE) algorithm, which we are going to cover in detail below.
Turning to the historical development of this approach for a moment, the paper that popularized the use of the byte-level BPE algorithm for language model tokenization is the [GPT-2 paper](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf) from OpenAI in 2019, "Language Models are Unsupervised Multitask Learners". Scroll down to Section 2.2 on "Input Representation" where they describe and motivate this algorithm. At the end of this section you'll see them say:
> *The vocabulary is expanded to 50,257. We also increase the context size from 512 to 1024 tokens and a larger batchsize of 512 is used.*
Recall that in the attention layer of a Transformer, every token is attending to a finite list of tokens previously in the sequence. The paper here says that the GPT-2 model has a context length of 1024 tokens, up from 512 in GPT-1. In other words, tokens are the fundamental "atoms" at the input to the LLM. And tokenization is the process for taking raw strings in Python and converting them to a list of tokens, and vice versa. As another popular example to demonstrate the pervasiveness of this abstraction, if you go to the [Llama 2](https://arxiv.org/abs/2307.09288) paper as well and you search for "token", you're going to get 63 hits. So for example, the paper claims that they trained on 2 trillion tokens, etc.
### Brief taste of the complexities of tokenization
Before we dive into details of the implementation, let's briefly motivate the need to understand the tokenization process in some detail. Tokenization is at the heart of a lot of weirdness in LLMs and I would advise that you do not brush it off. A lot of the issues that may look like issues with the neural network architecture actually trace back to tokenization. Here are just a few examples:
- Why can't LLM spell words? **Tokenization**.
- Why can't LLM do super simple string processing tasks like reversing a string? **Tokenization**.
- Why is LLM worse at non-English languages (e.g. Japanese)? **Tokenization**.
- Why is LLM bad at simple arithmetic? **Tokenization**.
- Why did GPT-2 have more than necessary trouble coding in Python? **Tokenization**.
- Why did my LLM abruptly halt when it sees the string "<|endoftext|>"? **Tokenization**.
- What is this weird warning I get about a "trailing whitespace"? **Tokenization**.
- Why did the LLM break if I ask it about "SolidGoldMagikarp"? **Tokenization**.
- Why should I prefer to use YAML over JSON with LLMs? **Tokenization**.
- Why is LLM not actually end-to-end language modeling? **Tokenization**.
- What is the real root of suffering? **Tokenization**.
We will loop back around to these at the end of the video.
### Visual preview of tokenization
Next, let's load this [tokenization webapp](https://tiktokenizer.vercel.app). What is nice about this webapp is that tokenization is running live in your web browser, allowing you to easily input some text string at the input, and see the tokenization on the right. On the top, you can see that we are currently using the `gpt2` tokenizer, and we see that the string that we pasted in with this example is currently tokenizing into 300 tokens. Here they are shown explicitly in colors:

So for example, the string "Tokenization" encoded into the tokens 30642 followed by the token 1634. The token " is" (note that these is three characters, including the space in the front, this is important!) is index 318. Be careful with whitespace because it is absolutely present in the string and must be tokenized along with all the other characters, but is usually omitted in visualization for clarity. You can toggle on and off its visualization at the bottom of the app. In the same way, the token " at" is 379, " the" is 262, etc.
Next, we have a simple example of some arithmetic. Here, we see that numbers may be inconsistently decomposed by the tokenizer. For example, the number 127 is a single token of three characters, but the number 677 because two tokens: the token " 6" (again, note the space in the front!) and the token "77". We rely on the large language model to make sense of this arbitrariness. It has to learn inside its parameters and during training that these two tokens (" 6" and "77" actually combine to create the number 677). In the same way, we see that if the LLM wanted to predict that the result of this sum is the number 804, it would have to output that in two time steps: first it has to emit the token " 8", and then the token "04". Note that all of these splits look completely arbitrary. In the example right below, we see that 1275 is "12" followed by "75", 6773 is actually two tokens " 6", "773", and 8041 is " 8", "041".
(to be continued...)
(TODO: may continue this unless we figure out how to generate it automatically from the video :))
================================================
FILE: minbpe/__init__.py
================================================
from .base import Tokenizer
from .basic import BasicTokenizer
from .regex import RegexTokenizer
from .gpt4 import GPT4Tokenizer
================================================
FILE: minbpe/base.py
================================================
"""
Contains the base Tokenizer class and a few common helper functions.
The base class also contains the (common) save/load functionality.
It would be possible to be a lot more strict about the interface and
e.g. isolating all regex/pattern parts to the RegexTokenizer, but
some concessions are made for simplicity.
"""
import unicodedata
# -----------------------------------------------------------------------------
# a few helper functions useful for both BasicTokenizer and RegexTokenizer
def get_stats(ids, counts=None):
"""
Given a list of integers, return a dictionary of counts of consecutive pairs
Example: [1, 2, 3, 1, 2] -> {(1, 2): 2, (2, 3): 1, (3, 1): 1}
Optionally allows to update an existing dictionary of counts
"""
counts = {} if counts is None else counts
for pair in zip(ids, ids[1:]): # iterate consecutive elements
counts[pair] = counts.get(pair, 0) + 1
return counts
def merge(ids, pair, idx):
"""
In the list of integers (ids), replace all consecutive occurrences
of pair with the new integer token idx
Example: ids=[1, 2, 3, 1, 2], pair=(1, 2), idx=4 -> [4, 3, 4]
"""
newids = []
i = 0
while i < len(ids):
# if not at the very last position AND the pair matches, replace it
if ids[i] == pair[0] and i < len(ids) - 1 and ids[i+1] == pair[1]:
newids.append(idx)
i += 2
else:
newids.append(ids[i])
i += 1
return newids
# first two helper functions...
def replace_control_characters(s: str) -> str:
# we don't want to print control characters
# which distort the output (e.g. \n or much worse)
# https://stackoverflow.com/questions/4324790/removing-control-characters-from-a-string-in-python/19016117#19016117
# http://www.unicode.org/reports/tr44/#GC_Values_Table
chars = []
for ch in s:
if unicodedata.category(ch)[0] != "C":
chars.append(ch) # this character is ok
else:
chars.append(f"\\u{ord(ch):04x}") # escape
return "".join(chars)
def render_token(t: bytes) -> str:
# pretty print a token, escaping control characters
s = t.decode('utf-8', errors='replace')
s = replace_control_characters(s)
return s
# -----------------------------------------------------------------------------
# the base Tokenizer class
class Tokenizer:
"""Base class for Tokenizers"""
def __init__(self):
# default: vocab size of 256 (all bytes), no merges, no patterns
self.merges = {} # (int, int) -> int
self.pattern = "" # str
self.special_tokens = {} # str -> int, e.g. {'<|endoftext|>': 100257}
self.vocab = self._build_vocab() # int -> bytes
def train(self, text, vocab_size, verbose=False):
# Tokenizer can train a vocabulary of size vocab_size from text
raise NotImplementedError
def encode(self, text):
# Tokenizer can encode a string into a list of integers
raise NotImplementedError
def decode(self, ids):
# Tokenizer can decode a list of integers into a string
raise NotImplementedError
def _build_vocab(self):
# vocab is simply and deterministically derived from merges
vocab = {idx: bytes([idx]) for idx in range(256)}
for (p0, p1), idx in self.merges.items():
vocab[idx] = vocab[p0] + vocab[p1]
for special, idx in self.special_tokens.items():
vocab[idx] = special.encode("utf-8")
return vocab
def save(self, file_prefix):
"""
Saves two files: file_prefix.vocab and file_prefix.model
This is inspired (but not equivalent to!) sentencepiece's model saving:
- model file is the critical one, intended for load()
- vocab file is just a pretty printed version for human inspection only
"""
# write the model: to be used in load() later
model_file = file_prefix + ".model"
with open(model_file, 'w') as f:
# write the version, pattern and merges, that's all that's needed
f.write("minbpe v1\n")
f.write(f"{self.pattern}\n")
# write the special tokens, first the number of them, then each one
f.write(f"{len(self.special_tokens)}\n")
for special, idx in self.special_tokens.items():
f.write(f"{special} {idx}\n")
# the merges dict
for idx1, idx2 in self.merges:
f.write(f"{idx1} {idx2}\n")
# write the vocab: for the human to look at
vocab_file = file_prefix + ".vocab"
inverted_merges = {idx: pair for pair, idx in self.merges.items()}
with open(vocab_file, "w", encoding="utf-8") as f:
for idx, token in self.vocab.items():
# note: many tokens may be partial utf-8 sequences
# and cannot be decoded into valid strings. Here we're using
# errors='replace' to replace them with the replacement char �.
# this also means that we couldn't possibly use .vocab in load()
# because decoding in this way is a lossy operation!
s = render_token(token)
# find the children of this token, if any
if idx in inverted_merges:
# if this token has children, render it nicely as a merge
idx0, idx1 = inverted_merges[idx]
s0 = render_token(self.vocab[idx0])
s1 = render_token(self.vocab[idx1])
f.write(f"[{s0}][{s1}] -> [{s}] {idx}\n")
else:
# otherwise this is leaf token, just print it
# (this should just be the first 256 tokens, the bytes)
f.write(f"[{s}] {idx}\n")
def load(self, model_file):
"""Inverse of save() but only for the model file"""
assert model_file.endswith(".model")
# read the model file
merges = {}
special_tokens = {}
idx = 256
with open(model_file, 'r', encoding="utf-8") as f:
# read the version
version = f.readline().strip()
assert version == "minbpe v1"
# read the pattern
self.pattern = f.readline().strip()
# read the special tokens
num_special = int(f.readline().strip())
for _ in range(num_special):
special, special_idx = f.readline().strip().split()
special_tokens[special] = int(special_idx)
# read the merges
for line in f:
idx1, idx2 = map(int, line.split())
merges[(idx1, idx2)] = idx
idx += 1
self.merges = merges
self.special_tokens = special_tokens
self.vocab = self._build_vocab()
================================================
FILE: minbpe/basic.py
================================================
"""
Minimal (byte-level) Byte Pair Encoding tokenizer.
Algorithmically follows along the GPT tokenizer:
https://github.com/openai/gpt-2/blob/master/src/encoder.py
But:
- Does not handle the regular expression splitting pattern.
- Does not handle any special tokens.
"""
from .base import Tokenizer, get_stats, merge
class BasicTokenizer(Tokenizer):
def __init__(self):
super().__init__()
def train(self, text, vocab_size, verbose=False):
assert vocab_size >= 256
num_merges = vocab_size - 256
# input text preprocessing
text_bytes = text.encode("utf-8") # raw bytes
ids = list(text_bytes) # list of integers in range 0..255
# iteratively merge the most common pairs to create new tokens
merges = {} # (int, int) -> int
vocab = {idx: bytes([idx]) for idx in range(256)} # int -> bytes
for i in range(num_merges):
# count up the number of times every consecutive pair appears
stats = get_stats(ids)
# find the pair with the highest count
pair = max(stats, key=stats.get)
# mint a new token: assign it the next available id
idx = 256 + i
# replace all occurrences of pair in ids with idx
ids = merge(ids, pair, idx)
# save the merge
merges[pair] = idx
vocab[idx] = vocab[pair[0]] + vocab[pair[1]]
# prints
if verbose:
print(f"merge {i+1}/{num_merges}: {pair} -> {idx} ({vocab[idx]}) had {stats[pair]} occurrences")
# save class variables
self.merges = merges # used in encode()
self.vocab = vocab # used in decode()
def decode(self, ids):
# given ids (list of integers), return Python string
text_bytes = b"".join(self.vocab[idx] for idx in ids)
text = text_bytes.decode("utf-8", errors="replace")
return text
def encode(self, text):
# given a string text, return the token ids
text_bytes = text.encode("utf-8") # raw bytes
ids = list(text_bytes) # list of integers in range 0..255
while len(ids) >= 2:
# find the pair with the lowest merge index
stats = get_stats(ids)
pair = min(stats, key=lambda p: self.merges.get(p, float("inf")))
# subtle: if there are no more merges available, the key will
# result in an inf for every single pair, and the min will be
# just the first pair in the list, arbitrarily
# we can detect this terminating case by a membership check
if pair not in self.merges:
break # nothing else can be merged anymore
# otherwise let's merge the best pair (lowest merge index)
idx = self.merges[pair]
ids = merge(ids, pair, idx)
return ids
================================================
FILE: minbpe/gpt4.py
================================================
"""
Implements the GPT-4 Tokenizer as a light wrapper around the RegexTokenizer.
Note that this is a pretrained tokenizer. By default and inside init(), it
loads the pretrained tokenizer from the `cl100k_base` tokenizer of tiktoken.
"""
import tiktoken
from .regex import RegexTokenizer
def bpe(mergeable_ranks, token, max_rank):
# helper function used in get_gpt4_merges() to reconstruct the merge forest
parts = [bytes([b]) for b in token]
while True:
min_idx = None
min_rank = None
for i, pair in enumerate(zip(parts[:-1], parts[1:])):
rank = mergeable_ranks.get(pair[0] + pair[1])
if rank is not None and (min_rank is None or rank < min_rank):
min_idx = i
min_rank = rank
if min_rank is None or (max_rank is not None and min_rank >= max_rank):
break
assert min_idx is not None
parts = parts[:min_idx] + [parts[min_idx] + parts[min_idx + 1]] + parts[min_idx + 2:]
return parts
def recover_merges(mergeable_ranks):
# the `merges` are already the byte sequences in their merged state.
# so we have to recover the original pairings. We can do this by doing
# a small BPE training run on all the tokens, in their order.
# also see https://github.com/openai/tiktoken/issues/60
# also see https://github.com/karpathy/minbpe/issues/11#issuecomment-1950805306
merges = {}
for token, rank in mergeable_ranks.items():
if len(token) == 1:
continue # skip raw bytes
pair = tuple(bpe(mergeable_ranks, token, max_rank=rank))
assert len(pair) == 2
# recover the integer ranks of the pair
ix0 = mergeable_ranks[pair[0]]
ix1 = mergeable_ranks[pair[1]]
merges[(ix0, ix1)] = rank
return merges
GPT4_SPLIT_PATTERN = r"""'(?i:[sdmt]|ll|ve|re)|[^\r\n\p{L}\p{N}]?+\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]++[\r\n]*|\s*[\r\n]|\s+(?!\S)|\s+"""
GPT4_SPECIAL_TOKENS = {
'<|endoftext|>': 100257,
'<|fim_prefix|>': 100258,
'<|fim_middle|>': 100259,
'<|fim_suffix|>': 100260,
'<|endofprompt|>': 100276
}
class GPT4Tokenizer(RegexTokenizer):
"""Lightweight wrapper on RegexTokenizer that matches GPT-4's tokenizer."""
def __init__(self):
super().__init__(pattern=GPT4_SPLIT_PATTERN)
# get the official tokenizer and its merges
enc = tiktoken.get_encoding("cl100k_base")
mergeable_ranks = enc._mergeable_ranks
# the merges are those of gpt4, but we have to recover them
self.merges = recover_merges(mergeable_ranks)
# reconstruct the vocab from the merges
vocab = {idx: bytes([idx]) for idx in range(256)}
for (p0, p1), idx in self.merges.items():
vocab[idx] = vocab[p0] + vocab[p1]
self.vocab = vocab
# now here is another tricky part.
# for some reason, the tokens corresponding to individual bytes
# are permuted in a different order. This is completely non-sensical
# and probably historical, but therefore we have to deal with it here.
self.byte_shuffle = {i: mergeable_ranks[bytes([i])] for i in range(256)}
self.inverse_byte_shuffle = {v: k for k, v in self.byte_shuffle.items()}
# finally register the special tokens
self.register_special_tokens(GPT4_SPECIAL_TOKENS)
def _encode_chunk(self, text_bytes):
# before we start processing bytes, we have to permute them
text_bytes = bytes(self.byte_shuffle[b] for b in text_bytes)
ids = super()._encode_chunk(text_bytes)
return ids
def decode(self, ids):
# we have to un-permute the bytes before we decode
text_bytes = b"".join(self.vocab[idx] for idx in ids)
text_bytes = bytes(self.inverse_byte_shuffle[b] for b in text_bytes)
text = text_bytes.decode("utf-8", errors="replace")
return text
# this is a pretrained tokenizer, it is not intended to be trained
def train(self, text, vocab_size, verbose=False):
raise NotImplementedError
# save/load would require some thought.
# we'd have to change save/load of base to add support for byte_shuffle...
# alternatively, we could move byte_shuffle to base class, but that would
# mean that we're making ugly our beautiful Tokenizer just to support
# the GPT-4 tokenizer and its weird historical quirks around byte_shuffle.
def save(self, file_prefix):
raise NotImplementedError("GPT4Tokenizer cannot be saved.")
def load(self, model_file):
raise NotImplementedError("GPT4Tokenizer cannot be loaded.")
def save_vocab(self, vocab_file):
# just for visualization purposes let's output the GPT-4 tokens
# in the exact same format as the base class would.
# simple run as:
# python -c "from minbpe import GPT4Tokenizer; GPT4Tokenizer().save_vocab('gpt4.vocab')"
from .base import render_token
# build vocab being mindful of the byte shuffle
vocab = {idx: bytes([self.inverse_byte_shuffle[idx]]) for idx in range(256)}
for (p0, p1), idx in self.merges.items():
vocab[idx] = vocab[p0] + vocab[p1]
# now merge the shuffled bytes and write to file
inverted_merges = {idx: pair for pair, idx in self.merges.items()}
with open(vocab_file, "w", encoding="utf-8") as f:
for idx, token in vocab.items():
s = render_token(token)
if idx in inverted_merges:
idx0, idx1 = inverted_merges[idx]
s0 = render_token(vocab[idx0])
s1 = render_token(vocab[idx1])
f.write(f"[{s0}][{s1}] -> [{s}] {idx}\n")
else:
f.write(f"[{s}] {idx}\n")
================================================
FILE: minbpe/regex.py
================================================
"""
Minimal (byte-level) Byte Pair Encoding tokenizer.
Algorithmically follows along the GPT tokenizer:
https://github.com/openai/gpt-2/blob/master/src/encoder.py
Unlike BasicTokenizer:
- RegexTokenizer handles an optional regex splitting pattern.
- RegexTokenizer handles optional special tokens.
"""
import regex as re
from .base import Tokenizer, get_stats, merge
# the main GPT text split patterns, see
# https://github.com/openai/tiktoken/blob/main/tiktoken_ext/openai_public.py
GPT2_SPLIT_PATTERN = r"""'(?:[sdmt]|ll|ve|re)| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""
GPT4_SPLIT_PATTERN = r"""'(?i:[sdmt]|ll|ve|re)|[^\r\n\p{L}\p{N}]?+\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]++[\r\n]*|\s*[\r\n]|\s+(?!\S)|\s+"""
class RegexTokenizer(Tokenizer):
def __init__(self, pattern=None):
"""
- pattern: optional string to override the default (GPT-4 split pattern)
- special_tokens: str -> int dictionary of special tokens
example: {'<|endoftext|>': 100257}
"""
super().__init__()
self.pattern = GPT4_SPLIT_PATTERN if pattern is None else pattern
self.compiled_pattern = re.compile(self.pattern)
self.special_tokens = {}
self.inverse_special_tokens = {}
def train(self, text, vocab_size, verbose=False):
assert vocab_size >= 256
num_merges = vocab_size - 256
# split the text up into text chunks
text_chunks = re.findall(self.compiled_pattern, text)
# input text preprocessing
ids = [list(ch.encode("utf-8")) for ch in text_chunks]
# iteratively merge the most common pairs to create new tokens
merges = {} # (int, int) -> int
vocab = {idx: bytes([idx]) for idx in range(256)} # idx -> bytes
for i in range(num_merges):
# count the number of times every consecutive pair appears
stats = {}
for chunk_ids in ids:
# passing in stats will update it in place, adding up counts
get_stats(chunk_ids, stats)
# find the pair with the highest count
pair = max(stats, key=stats.get)
# mint a new token: assign it the next available id
idx = 256 + i
# replace all occurrences of pair in ids with idx
ids = [merge(chunk_ids, pair, idx) for chunk_ids in ids]
# save the merge
merges[pair] = idx
vocab[idx] = vocab[pair[0]] + vocab[pair[1]]
# prints
if verbose:
print(f"merge {i+1}/{num_merges}: {pair} -> {idx} ({vocab[idx]}) had {stats[pair]} occurrences")
# save class variables
self.merges = merges # used in encode()
self.vocab = vocab # used in decode()
def register_special_tokens(self, special_tokens):
# special_tokens is a dictionary of str -> int
# example: {"<|endoftext|>": 100257}
self.special_tokens = special_tokens
self.inverse_special_tokens = {v: k for k, v in special_tokens.items()}
def decode(self, ids):
# given ids (list of integers), return Python string
part_bytes = []
for idx in ids:
if idx in self.vocab:
part_bytes.append(self.vocab[idx])
elif idx in self.inverse_special_tokens:
part_bytes.append(self.inverse_special_tokens[idx].encode("utf-8"))
else:
raise ValueError(f"invalid token id: {idx}")
text_bytes = b"".join(part_bytes)
text = text_bytes.decode("utf-8", errors="replace")
return text
def _encode_chunk(self, text_bytes):
# return the token ids
# let's begin. first, convert all bytes to integers in range 0..255
ids = list(text_bytes)
while len(ids) >= 2:
# find the pair with the lowest merge index
stats = get_stats(ids)
pair = min(stats, key=lambda p: self.merges.get(p, float("inf")))
# subtle: if there are no more merges available, the key will
# result in an inf for every single pair, and the min will be
# just the first pair in the list, arbitrarily
# we can detect this terminating case by a membership check
if pair not in self.merges:
break # nothing else can be merged anymore
# otherwise let's merge the best pair (lowest merge index)
idx = self.merges[pair]
ids = merge(ids, pair, idx)
return ids
def encode_ordinary(self, text):
"""Encoding that ignores any special tokens."""
# split text into chunks of text by categories defined in regex pattern
text_chunks = re.findall(self.compiled_pattern, text)
# all chunks of text are encoded separately, then results are joined
ids = []
for chunk in text_chunks:
chunk_bytes = chunk.encode("utf-8") # raw bytes
chunk_ids = self._encode_chunk(chunk_bytes)
ids.extend(chunk_ids)
return ids
def encode(self, text, allowed_special="none_raise"):
"""
Unlike encode_ordinary, this function handles special tokens.
allowed_special: can be "all"|"none"|"none_raise" or a custom set of special tokens
if none_raise, then an error is raised if any special token is encountered in text
this is the default tiktoken behavior right now as well
any other behavior is either annoying, or a major footgun
"""
# decode the user desire w.r.t. handling of special tokens
special = None
if allowed_special == "all":
special = self.special_tokens
elif allowed_special == "none":
special = {}
elif allowed_special == "none_raise":
special = {}
assert all(token not in text for token in self.special_tokens)
elif isinstance(allowed_special, set):
special = {k: v for k, v in self.special_tokens.items() if k in allowed_special}
else:
raise ValueError(f"allowed_special={allowed_special} not understood")
if not special:
# shortcut: if no special tokens, just use the ordinary encoding
return self.encode_ordinary(text)
# otherwise, we have to be careful with potential special tokens in text
# we handle special tokens by splitting the text
# based on the occurrence of any exact match with any of the special tokens
# we can use re.split for this. note that surrounding the pattern with ()
# makes it into a capturing group, so the special tokens will be included
special_pattern = "(" + "|".join(re.escape(k) for k in special) + ")"
special_chunks = re.split(special_pattern, text)
# now all the special characters are separated from the rest of the text
# all chunks of text are encoded separately, then results are joined
ids = []
for part in special_chunks:
if part in special:
# this is a special token, encode it separately as a special case
ids.append(special[part])
else:
# this is an ordinary sequence, encode it normally
ids.extend(self.encode_ordinary(part))
return ids
================================================
FILE: requirements.txt
================================================
regex
tiktoken
================================================
FILE: tests/__init__.py
================================================
================================================
FILE: tests/taylorswift.txt
================================================
Copy paste of the Wikipedia article on Taylor Swift, as of Feb 16, 2024.
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Taylor Swift
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From Wikipedia, the free encyclopedia
For the album, see Taylor Swift (album).
Taylor Swift
Portrait of Taylor Swift in a cocktail dress
Swift at the 2023 MTV Video Music Awards
Born Taylor Alison Swift
December 13, 1989 (age 34)
West Reading, Pennsylvania, US
Occupations
Singer-songwriter producer director businesswoman actress
Years active 2004–present
Works
Albumssinglessongsvideosperformances
Relatives
Austin Swift (brother)
Marjorie Finlay (grandmother)
Awards Full list
Musical career
Origin Nashville, Tennessee, US
Genres
Pop country folk rock alternative
Instruments
Vocals guitar banjo piano ukulele
Labels
RCA Republic Big Machine
Website www.taylorswift.com Edit this at Wikidata
Signature
Taylor Alison Swift (born December 13, 1989) is an American singer-songwriter. Her versatile artistry, songwriting, and entrepreneurship have influenced the music industry, popular culture, and politics, and her life is a subject of widespread media coverage.
Swift began professional songwriting at 14 and signed with Big Machine Records in 2005 to become a country singer. She released six studio albums under the label, four of them to country radio, starting with Taylor Swift (2006). Her next, Fearless (2008), explored country pop, and its singles "Love Story" and "You Belong with Me" catapulted her to mainstream fame. Speak Now (2010) infused rock influences, while Red (2012) experimented with electronic elements and featured Swift's first Billboard Hot 100 number-one song, "We Are Never Ever Getting Back Together". She departed from her country image with 1989 (2014), a synth-pop album supported by the chart-topping songs "Shake It Off", "Blank Space", and "Bad Blood". Media scrutiny inspired the hip-hop-influenced Reputation (2017) and its number-one single "Look What You Made Me Do".
After signing with Republic Records in 2018, Swift released the eclectic pop album Lover (2019) and the autobiographical documentary Miss Americana (2020). She explored indie folk styles on the 2020 albums Folklore and Evermore, subdued electropop on Midnights (2022), and re-recorded four albums subtitled Taylor's Version after a dispute with Big Machine. These albums spawned the number-one songs "Cruel Summer", "Cardigan", "Willow", "Anti-Hero", "All Too Well", and "Is It Over Now?". Her Eras Tour (2023–2024) and its accompanying concert film became the highest-grossing tour and concert film of all time, respectively. Swift has directed several music videos and films such as Folklore: The Long Pond Studio Sessions (2020) and All Too Well: The Short Film (2021).
One of the world's best-selling musicians, with over 200 million records sold as of 2019, Swift has been named Global Recording Artist of the Year three times by the International Federation of the Phonographic Industry, whereas six of her albums have opened with over a million sales in a week. She is the highest-grossing female touring act, the most-streamed woman on Spotify and Apple Music, and the first billionaire with music as the main source of income. The 2023 Time Person of the Year, Swift has appeared on lists such as Rolling Stone's 100 Greatest Songwriters of All Time, Billboard's Greatest of All Time Artists, and Forbes' World's 100 Most Powerful Women. Her accolades include 14 Grammy Awards (featuring a record four Album of the Year wins), a Primetime Emmy Award, 40 American Music Awards, 40 Billboard Music Awards, and 23 MTV Video Music Awards.
Life and career
Early life
Swift's childhood home in Wyomissing, Pennsylvania
Taylor Alison Swift was born on December 13, 1989,[1] in West Reading, Pennsylvania.[2] She is named after singer-songwriter James Taylor.[3] Her father, Scott Kingsley Swift, is a former stockbroker for Merrill Lynch[4] and her mother, Andrea Gardner Swift (née Finlay), worked for a time as a mutual fund marketing executive.[5] Taylor has a younger brother, actor Austin Swift.[6]
Swift's mother is of Scottish and German descent, and her father is of Scottish and English descent with distant Italian ancestry.[7][8] Swift's paternal great-great-grandfather, Charles Carmine Antonio Baldi, was an Italian immigrant entrepreneur and community leader who opened several businesses in Philadelphia in the 1800s.[9][10][8] Her maternal grandmother, Marjorie (née Moehlenkamp) Finlay, was an opera singer.[11]
Swift spent her early years on a Christmas tree farm that her father had purchased from one of his clients.[12][13] She is a Christian.[14] She attended preschool and kindergarten at Alvernia Montessori School, run by Bernardine Franciscan sisters,[15] before transferring to the Wyndcroft School.[16] The family moved to a rented house in Wyomissing, Pennsylvania,[17] where Swift attended Wyomissing Area Junior/Senior High School.[18]
At age nine, Swift became interested in musical theater and performed in four Berks Youth Theatre Academy productions.[19] She also traveled regularly to New York City for vocal and acting lessons.[20] Swift later shifted her focus toward country music, inspired by Shania Twain's songs, which made her "want to just run around the block four times and daydream about everything".[21] She spent weekends performing at local festivals and events.[22][23] After watching a documentary about Faith Hill, Swift felt she needed to move to Nashville, Tennessee, to pursue a career in music.[24] She traveled there with her mother at age eleven to visit record labels and submitted demo tapes of Dolly Parton and Dixie Chicks karaoke covers.[25] She was rejected, however, because "everyone in that town wanted to do what I wanted to do. So, I kept thinking to myself, I need to figure out a way to be different."[26] She spent summers in Stone Harbor, New Jersey until she was 14 years old, performing in a local coffee shop.[27][28]
When Swift was around 12 years old, musician Ronnie Cremer taught her to play guitar. Cremer helped with her first efforts as a songwriter, leading her to write "Lucky You".[29] In 2003, Swift and her parents started working with New York–based talent manager Dan Dymtrow. With his help, Swift modeled for Abercrombie & Fitch as part of their "Rising Stars" campaign, had an original song included on a Maybelline compilation CD, and met with major record labels.[30] After performing original songs at an RCA Records showcase, Swift, then 13 years old, was given an artist development deal and began making frequent trips to Nashville with her mother.[31][32][33] To help Swift break into the country music scene, her father transferred to Merrill Lynch's Nashville office when she was 14 years old, and the family relocated to Hendersonville, Tennessee.[12][34] Swift attended Hendersonville High School[35] before transferring to Aaron Academy after two years, which better accommodated her touring schedule through homeschooling. She graduated one year early.[36][37]
2004–2008: Career beginnings and first album
In Nashville, Swift worked with experienced Music Row songwriters such as Troy Verges, Brett Beavers, Brett James, Mac McAnally, and the Warren Brothers[38][39] and formed a lasting working relationship with Liz Rose.[40] They began meeting for two-hour writing sessions every Tuesday afternoon after school.[41] Rose called the sessions "some of the easiest I've ever done. Basically, I was just her editor. She'd write about what happened in school that day. She had such a clear vision of what she was trying to say. And she'd come in with the most incredible hooks." Swift became the youngest artist signed by the Sony/ATV Tree publishing house,[42] but left then BMG-owned RCA Records (later bought by Sony Music) at the age of 14 due to the label's lack of care and them "cut[ting] other people's stuff". She was also concerned that development deals can shelve artists[33][23] and recalled: "I genuinely felt that I was running out of time. I wanted to capture these years of my life on an album while they still represented what I was going through."[43]
Taylor Swift singing on a microphone and playing a guitar
Swift opening for Brad Paisley in 2007. To promote her first album, she opened tours for other country musicians in 2007 and 2008.[44]
At an industry showcase at Nashville's Bluebird Cafe in 2005, Swift caught the attention of Scott Borchetta, a DreamWorks Records executive who was preparing to form an independent record label, Big Machine Records. She had first met Borchetta in 2004.[45] She was one of Big Machine's first signings,[33] and her father purchased a three-percent stake in the company for an estimated $120,000.[46][47] She began working on her eponymous debut album with Nathan Chapman.[23] Swift wrote or co-wrote all album tracks, and co-writers included Rose, Robert Ellis Orrall, Brian Maher, and Angelo Petraglia.[48] Taylor Swift was released on October 24, 2006.[49] Country Weekly critic Chris Neal deemed Swift better than previous aspiring teenage country singers because of her "honesty, intelligence and idealism".[50] The album peaked at number five on the US Billboard 200, on which it spent 157 weeks—the longest stay on the chart by any release in the US in the 2000s decade.[51] Swift became the first female country music artist to write or co-write every track on a US platinum-certified debut album.[52]
Big Machine Records was still in its infancy during the June 2006 release of the lead single, "Tim McGraw", which Swift and her mother helped promote by packaging and sending copies of the CD single to country radio stations. As there was not enough furniture at the label yet, they would sit on the floor to do so.[53] She spent much of 2006 promoting Taylor Swift with a radio tour and television appearances; she opened for Rascal Flatts on select dates during their 2006 tour,[54] as a replacement for Eric Church.[55] Borchetta said that although record industry peers initially disapproved of his signing a 15-year-old singer-songwriter, Swift tapped into a previously unknown market—teenage girls who listen to country music.[53][12]
Following "Tim McGraw", four more singles were released throughout 2007 and 2008: "Teardrops on My Guitar", "Our Song", "Picture to Burn" and "Should've Said No". All appeared on Billboard's Hot Country Songs, with "Our Song" and "Should've Said No" reaching number one. With "Our Song", Swift became the youngest person to single-handedly write and sing a number-one song on the chart.[56] "Teardrops on My Guitar" reached number thirteen on the US Billboard Hot 100.[57] Swift also released two EPs, The Taylor Swift Holiday Collection in October 2007 and Beautiful Eyes in July 2008.[58][59] She promoted her debut album extensively as the opening act for other country musicians' tours in 2006 and 2007, including those by George Strait,[60] Brad Paisley,[61] and Tim McGraw and Faith Hill.[62]
Swift won multiple accolades for Taylor Swift. She was one of the recipients of the Nashville Songwriters Association's Songwriter/Artist of the Year in 2007, becoming the youngest person given the title.[63] She also won the Country Music Association's Horizon Award for Best New Artist,[64] the Academy of Country Music Awards' Top New Female Vocalist,[65] and the American Music Awards' Favorite Country Female Artist honor.[66] She was also nominated for Best New Artist at the 50th Annual Grammy Awards.[67] In 2008, she opened for Rascal Flatts again[68] and briefly dated the singer Joe Jonas.[69][70]
2008–2010: Fearless
Taylor Swift in 2009
Swift at the 2009 premiere of Hannah Montana: The Movie. She had a cameo appearance in the film and wrote two songs for its soundtrack.[71][72]
Swift's second studio album, Fearless, was released on November 11, 2008, in North America,[73] and in March 2009 in other markets.[74] Critics lauded Swift's honest and vulnerable songwriting in contrast to other teenage singers.[75] Five singles were released in 2008–2009: "Love Story", "White Horse", "You Belong with Me", "Fifteen", and "Fearless". The first single peaked at number four on the Billboard Hot 100 and number one in Australia.[57][76] It was the first country song to top Billboard's Pop Songs chart.[77] "You Belong with Me" was the album's highest-charting single on the Billboard Hot 100, peaking at number two,[78] and was the first country song to top Billboard's all-genre Radio Songs chart.[79] All five singles were Hot Country Songs top-10 entries, with "Love Story" and "You Belong with Me" topping the chart.[80] Fearless became her first number-one album on the Billboard 200 and 2009's top-selling album in the US.[81] The Fearless Tour, Swift's first headlining concert tour, grossed over $63 million.[82] Journey to Fearless, a documentary miniseries, aired on television and was later released on DVD and Blu-ray.[83] Swift performed as a supporting act for Keith Urban's Escape Together World Tour in 2009.[84]
In 2009, the music video for "You Belong with Me" was named Best Female Video at the 2009 MTV Video Music Awards.[85] Her acceptance speech was interrupted by rapper Kanye West,[86] an incident that became the subject of controversy, widespread media attention and Internet memes.[87] That year she won five American Music Awards, including Artist of the Year and Favorite Country Album.[88] Billboard named her 2009's Artist of the Year.[89] She won Video of the Year and Female Video of the Year for "Love Story" at the 2009 CMT Music Awards, where she made a parody video of the song with rapper T-Pain called "Thug Story".[90] At the 52nd Annual Grammy Awards, Fearless was named Album of the Year and Best Country Album, and "White Horse" won Best Country Song and Best Female Country Vocal Performance. Swift was the youngest artist to win Album of the Year.[note 1] At the 2009 Country Music Association Awards, Swift won Album of the Year for Fearless and was named Entertainer of the Year, the youngest person to win the honor.[93]
Swift featured on John Mayer's single "Half of My Heart" and Boys Like Girls' single "Two Is Better Than One", the latter of which she co-wrote.[94][95] She co-wrote and recorded "Best Days of Your Life" with Kellie Pickler,[96] and wrote two songs for the Hannah Montana: The Movie soundtrack—"You'll Always Find Your Way Back Home" and "Crazier".[72] She contributed two songs to the Valentine's Day soundtrack, including the single "Today Was a Fairytale", which was her first number-one on the Canadian Hot 100 and peaked at number two on the US Hot 100.[97][98] While shooting her film debut Valentine's Day in October 2009, Swift dated co-star Taylor Lautner.[99] In 2009, she made her television debut as a rebellious teenager in an CSI: Crime Scene Investigation episode,[100] and she hosted and performed as the musical guest on Saturday Night Live; she was the first host ever to write their own opening monologue.[101][102]
2010–2014: Speak Now and Red
Swift singing into a mic while playing a banjo
Swift performing at the Speak Now World Tour in 2012
In August 2010, Swift released "Mine", the lead single from her third studio album, Speak Now. The single entered the Hot 100 at number three.[103] Swift wrote the album alone and co-produced every track.[104] The album was released on October 25, 2010,[105] opening atop the Billboard 200 with over one million copies sold.[106] It became the fastest-selling digital album by a female artist, with 278,000 downloads in a week.[107] Critics appreciated Swift's grown-up perspectives:[108] Rob Sheffield of Rolling Stone wrote, "in a mere four years, the 20-year-old Nashville firecracker has put her name on three dozen or so of the smartest songs released by anyone in pop, rock or country."[109] "Back to December", "Mean", "The Story of Us", "Sparks Fly", and "Ours" became subsequent singles, with the latter two reaching number one on the Hot Country Songs[80] and the first two peaking in the top ten in Canada.[98] She dated actor Jake Gyllenhaal in 2010.[110]
At the 54th Annual Grammy Awards in 2012, Swift won Best Country Song and Best Country Solo Performance for "Mean", which she performed during the ceremony.[111] Swift won other awards for Speak Now, including Songwriter/Artist of the Year by the Nashville Songwriters Association (2010 and 2011),[112][113] Woman of the Year by Billboard (2011),[114] and Entertainer of the Year by the Academy of Country Music (2011 and 2012)[115] and the Country Music Association in 2011.[116] At the American Music Awards of 2011, Swift won Artist of the Year and Favorite Country Album.[117] Rolling Stone named Speak Now amongst its "50 Best Female Albums of All Time" (2012), writing: "She might get played on the country station, but she's one of the few genuine rock stars we've got these days, with a flawless ear for what makes a song click."[118]
The Speak Now World Tour ran from February 2011 to March 2012 and grossed over $123 million,[119] followed up by the live album, Speak Now World Tour: Live.[120] She contributed two original songs to The Hunger Games soundtrack album: "Eyes Open" and "Safe & Sound", co-written and recorded with the Civil Wars and T-Bone Burnett. "Safe & Sound" won the Grammy Award for Best Song Written for Visual Media and was nominated for the Golden Globe Award for Best Original Song.[121][122] Swift featured on B.o.B's single "Both of Us", released in May 2012.[123] She dated Conor Kennedy that year.[124]
Taylor Swift on the Red Tour
Swift on the Red Tour (2013)
In August 2012, Swift released "We Are Never Ever Getting Back Together", the lead single from her fourth studio album, Red. It became her first number one single in the US and New Zealand,[125][126] and became the fastest-selling single in digital history.[127] Other singles from the album were "Begin Again", "I Knew You Were Trouble", "22", "Everything Has Changed", "The Last Time", and "Red". "I Knew You Were Trouble" reached the top five on charts in Australia, Canada, Denmark, Ireland, New Zealand, the UK and the US.[128] "Begin Again", "22", and "Red" reached the top 20 in the US.[57] On Red, released on October 22, 2012,[129] Swift worked with Chapman and Rose, as well as the new producers Max Martin and Shellback.[130] It incorporated many pop and rock styles such as heartland rock, dubstep and dance-pop.[131] Randall Roberts of Los Angeles Times said Swift "strives for something much more grand and accomplished" with Red.[132] It opened at number one on the Billboard 200 with 1.21 million sales.[133] Red was Swift's first number-one album in the UK.[134] It earned several accolades, including four nominations at the 56th Annual Grammy Awards (2014).[135] Swift received American Music Awards for Best Female Country Artist in 2012, Artist of the Year in 2013,[136][137] and the Nashville Songwriters Association's Songwriter/Artist Award for the fifth and sixth consecutive years.[138] The Red Tour ran from March 2013 to June 2014 and grossed over $150 million, becoming the highest-grossing country tour ever.[139] Swift was honored with the Pinnacle Award, making her the second recipient of the accolade after Garth Brooks.[140] During this time, she briefly dated the English singer Harry Styles.[141]
In 2013, Swift recorded "Sweeter than Fiction", a song she wrote and produced with Jack Antonoff for the One Chance soundtrack. The song received a Best Original Song nomination at the 71st Golden Globe Awards.[142] She provided guest vocals for Tim McGraw's song "Highway Don't Care", also featuring Keith Urban.[143] Swift performed "As Tears Go By" with the Rolling Stones in Chicago, Illinois, as part of the band's 50 & Counting tour,[144] and joined Florida Georgia Line at their set at the 2013 Country Radio Seminar to sing "Cruise".[145] Swift voiced Audrey in the animated film The Lorax (2012),[146] made a cameo in the sitcom New Girl (2013),[147] and had a supporting role in the dystopian film The Giver (2014).[148]
2014–2018: 1989 and Reputation
Swift performing on a mic, dressed in a blue skirt
Swift at the 1989 World Tour, the highest-grossing tour of 2015
In March 2014, Swift began living in New York City.[note 2] She hired Tree Paine as her publicist[151] and worked on her fifth studio album, 1989, with the producers Jack Antonoff, Max Martin, Shellback, Imogen Heap, Ryan Tedder, and Ali Payami.[152] She promoted the album extensively, including inviting fans to secret album-listening sessions.[153] 1989 was released on October 27, 2014, and opened atop the Billboard 200 with 1.28 million copies sold.[154] Its singles "Shake It Off", "Blank Space" and "Bad Blood" reached number one in Australia, Canada and the US, the first two making Swift the first woman to replace herself at the Hot 100 top spot;[155] other singles include "Style", "Wildest Dreams", "Out of the Woods" and "New Romantics".[156] The 1989 World Tour (2015) was the highest-grossing tour of the year with $250 million in total revenue.[157]
Prior to 1989's release, Swift stressed the importance of albums to artists and fans.[158] In November 2014, she removed her entire catalog from Spotify, arguing that its ad-supported, free service undermined the premium service, which provides higher royalties for songwriters.[159] In a June 2015 open letter, Swift criticized Apple Music for not offering royalties to artists during the streaming service's free three-month trial period and stated that she would pull 1989 from the catalog.[160] The following day, Apple Inc. announced that it would pay artists during the free trial period,[161] and Swift agreed to let 1989 on the streaming service.[162] She then returned her entire catalog plus 1989 to Spotify, Amazon Music and Google Play and other digital streaming platforms in June 2017.[163] Swift was named Billboard's Woman of the Year in 2014, becoming the first artist to win the award twice.[164] At the 2014 American Music Awards, Swift received the inaugural Dick Clark Award for Excellence.[165] On her 25th birthday in 2014, the Grammy Museum at L.A. Live opened an exhibit in her honor in Los Angeles that ran until October 4, 2015, and broke museum attendance records.[166][167] In 2015, Swift won the Brit Award for International Female Solo Artist.[168] The video for "Bad Blood" won Video of the Year and Best Collaboration at the 2015 MTV Video Music Awards.[169] At the 58th Grammy Awards (2016), 1989 won Album of the Year and Best Pop Vocal Album, making Swift the first woman and fifth act overall to win Album of the Year twice.[170]
Swift wearing a sparkling blazer singing on a mic
Swift on her Reputation Stadium Tour (2018), the highest-grossing North American tour ever
Swift dated the Scottish DJ Calvin Harris from March 2015 to June 2016.[171] They co-wrote the song "This Is What You Came For", featuring vocals from the Barbadian singer Rihanna; Swift was initially credited under the pseudonym Nils Sjöberg.[172] In April 2016, Swift criticized the lyrics of Kanye West's single "Famous", in which he sings "I made that bitch famous" in reference to his interruption of her acceptance speech at the 2009 MTV Video Music Awards. West claimed he had received her approval for the line, and his then-wife Kim Kardashian released video clips of Swift and West discussing the single amicably over the phone; a full recording leaked in 2020 established that West did not disclose that he would call her a "bitch".[173][174]
After briefly dating the English actor Tom Hiddleston,[175] Swift entered a six-year relationship with the English actor Joe Alwyn in September 2016.[176][177][178] She wrote the song "Better Man" for the band Little Big Town, which earned her the Song of the Year award at the 51st CMA Awards.[179] Swift and English singer Zayn Malik released the joint single "I Don't Wanna Live Forever" for Fifty Shades Darker: Original Motion Picture Soundtrack (2017). The song reached number two in the US.[180]
In August 2017, Swift successfully countersued David Mueller, a former radio jockey for KYGO-FM, who sued her for damages from loss of employment. Four years earlier, she informed Mueller's bosses that he had sexually assaulted her by groping her at an event.[181] Also that month, after a one-year hiatus from the spotlight, Swift cleared her social media accounts and released "Look What You Made Me Do" as the lead single from her sixth album, Reputation.[182][183] The single was Swift's first UK number-one single.[184] It topped charts in Australia, Ireland, New Zealand, and the US.[185] Reputation, released on November 10, 2017,[186] incorporated electropop, hip hop, R&B, and EDM.[187] Reviews praised Swift's mature artistry, but some denounced the themes of fame and gossip.[188] The album opened atop the Billboard 200 with 1.21 million US sales[189] and topped the charts in the UK, Australia, and Canada.[190] Its singles "...Ready for It?", "End Game" (featuring Ed Sheeran and Future), and "Delicate" were released to pop radio.[191] Reputation was nominated for a Grammy Award for Best Pop Vocal Album.[192] Swift featured on the country duo Sugarland's "Babe" (2018).[193]
At the 2018 American Music Awards, Swift won four awards, which made her accumulate 23 trophies in total and become the AMAs' most awarded female musician, surpassing Whitney Houston.[194] The same year, she embarked on her Reputation Stadium Tour,[195] which became the highest-grossing North American concert tour in history and grossed $345.7 million worldwide.[196]
2018–2020: Lover, Folklore, and Evermore
In November 2018, she signed a new deal with the Universal Music Group; her subsequent releases were promoted by Republic Records. Swift said the contract included a provision for her to maintain ownership of her masters. In addition, in the event that Universal sold any part of its stake in Spotify, it agreed to distribute a non-recoupable portion of the proceeds among its artists.[197] Vox called it a huge commitment from Universal, which was "far from assured" until Swift intervened.[198]
A portrait of Swift
Swift at the American Music Awards of 2019, where she was named Artist of the Decade
Swift's first album with Republic Records, Lover, was released on August 23, 2019.[199] Besides Antonoff, she worked with Louis Bell, Frank Dukes, and Joel Little.[200] Lover was her sixth consecutive album to sell more than 500,000 US copies in one week.[201] Critics commended the album's free-spirited mood and emotional intimacy.[202][203] The singles "Me!" and "You Need to Calm Down" both peaked at number two on the Hot 100,[204] and other singles were the top-10 single "Lover", the top-40 single "The Man",[57] and the 2023 resurgent success, chart topper "Cruel Summer".[205] Lover was the world's best-selling album by a solo artist of 2019,[206] and along with its singles earned nominations at the 62nd Annual Grammy Awards in 2020.[207] At the 2019 MTV Video Music Awards, "Me!" won Best Visual Effects, and "You Need to Calm Down" won Video of the Year and Video for Good. Swift was the first female and second artist overall to win Video of the Year for a video that they directed.[208]
While promoting Lover, Swift became embroiled in a public dispute with the talent manager Scooter Braun and Big Machine over the purchase of the masters of her back catalog.[209][210] Swift said she had been trying to buy the masters, but Big Machine would only allow her to do so if she exchanged one new album for each older one under a new contract, which she refused to sign.[209][211] Swift began re-recording her back catalog in November 2020.[212] Besides music, she played Bombalurina in the film adaptation of Andrew Lloyd Webber's musical Cats (2019), for which she co-wrote and recorded the Golden Globe-nominated original song "Beautiful Ghosts".[213][214] Critics panned the film but praised Swift's performance.[215] The documentary Miss Americana, which chronicled parts of Swift's life and career, premiered at the 2020 Sundance Film Festival.[216] Swift signed a global publishing deal with Universal Music Publishing Group in February 2020 after her 16-year contract with Sony/ATV expired.[217]
Amidst the COVID-19 pandemic in 2020, Swift surprise-released two "sister albums" that she recorded with Antonoff and Aaron Dessner: Folklore on July 24, and Evermore on December 11.[218][219] Alwyn co-wrote and co-produced a few songs under the pseudonym William Bowery.[220] Both explore indie folk with a more muted production compared to her previous upbeat pop songs[221][222] and earned Swift widespread critical acclaim and artistic recognition.[223][224] Each album was supported by three singles catering to US pop, country, and triple A radio formats. The singles were "Cardigan", "Betty", and "Exile" from Folklore, and "Willow", "No Body, No Crime", and "Coney Island" from Evermore.[225] Folklore made Swift the first woman to win the Grammy Award for Album of the Year three times at the 63rd Annual Grammy Awards[226] and was the best-selling album of 2020 in the US.[227] Swift became the first artist to debut a US number-one album and a number-one song at the same time with Folklore's "Cardigan".[228] At the 2020 American Music Awards, she won three awards, including Artist of the Year for a record third consecutive time.[229] According to Billboard, she was 2020's highest-paid musician in the US and highest-paid solo musician worldwide.[230]
2020–2023: Re-recordings and Midnights
Swift performing in 2022
Following the masters dispute, Swift released re-recordings of her first six studio albums, beginning with Fearless (Taylor's Version) and Red (Taylor's Version) in April and November 2021, respectively. Both peaked atop the Billboard 200,[231] and the former was the first re-recorded album to do so.[232] Fearless (Taylor's Version) was preceded by "Love Story (Taylor's Version)", which made her the second artist after Dolly Parton to have both the original and re-recorded versions of a song reach number one on the Hot Country Songs chart.[233] Red (Taylor's Version) was supported by "All Too Well (10 Minute Version)", which became the longest song in history to top the Hot 100.[234] The song was accompanied by a short film, which won a Grammy Award for Best Music Video[235] and Swift's record third MTV Video Music Award for Video of the Year.[236]
Swift's tenth studio album, Midnights, was released on October 21, 2022.[237] Characterized by a restrained electropop[238][239] and synth-pop[240] sound, the album was dubbed by Rolling Stone critics as an instant classic.[241][242] The album was her fifth to open atop the Billboard 200 with first-week sales of over one million copies and broke various sales and streaming records,[243] including the most single-day streams and most single-week streams on Spotify.[244] Its tracks, led by single "Anti-Hero", monopolized the top 10 of the Hot 100, making Swift the first artist to do so.[245] Two other singles, "Lavender Haze" and "Karma", peaked at number two on the Hot 100.[246] Swift won nine awards at the 2023 MTV Video Music Awards, including Video of the Year ("Anti-Hero") for a record fourth time.[247] At the 66th Annual Grammy Awards, she received Best Pop Vocal Album, and her fourth Album of the Year—the most for any artist.[248]
Swift released the third re-recorded album, Speak Now (Taylor's Version), on July 7, 2023, becoming the woman with the most number-one albums (12) in Billboard 200 history, surpassing Barbra Streisand.[249] 1989 (Taylor's Version), released on October 27, 2023, became Swift's record-extending sixth album to sell one million copies in a single week in the US and surpassed Midnights for her career's largest album sales week.[250] Its single "Is It Over Now?" debuted atop the Billboard Hot 100. Swift was 2023's most streamed artist on Spotify,[251] Apple Music,[252] and Amazon Music;[253] the first act to place number one on the year-end Billboard top artists list in three different decades (2009, 2015 and 2023);[254] and the first living artist to simultaneously chart five albums in the top 10 of the Billboard 200.[255] She had five out of the 10 best-selling albums of 2023 in the United States, a record since Luminate began tracking US music sales in 1991.[256][257]
Beyond her albums, Swift featured on five songs from 2021 to 2023: "Renegade" and "Birch" by Big Red Machine,[258] a remix of "Gasoline" by Haim,[259] "The Joker and the Queen" by Ed Sheeran,[260] and "The Alcott" by the National.[261] For the soundtrack of the 2022 film Where the Crawdads Sing, she recorded "Carolina", which received nominations for Best Original Song at the Golden Globes and Best Song Written for Visual Media at the Grammy Awards.[262] Outside of music, Swift had a supporting role in the 2022 period comedy film Amsterdam and has signed to direct an upcoming feature film for Searchlight Pictures.[263][264]
2023–present: The Eras Tour and The Tortured Poets Department
Swift singing into a mic
Swift on the Eras Tour in 2023
In March 2023, Swift embarked on the Eras Tour, a retrospective tour covering all her studio albums. Media outlets extensively covered the tour's cultural and economic impact,[265] and its US leg broke the record for the most tickets sold in a day.[245] Ticketmaster received public and political criticisms for mishandling the tour's ticket sales.[266] The Eras Tour became the highest-grossing tour in history, collecting over $1 billion.[267][268] Its concert film, released to theaters worldwide on October 13, 2023, grossed over $250 million to become the highest-grossing concert film, and was nominated for the Golden Globe Award for Cinematic and Box Office Achievement.[269][270] Swift's music releases, touring, and related activities culminated in an unprecedented height of popularity post-pandemic.[271] Music Business Worldwide remarked that she entered a "new stratosphere of global career success" in 2023.[272]
Swift began dating Kansas City Chiefs' tight end Travis Kelce in 2023.[273] In January 2024, AI-generated fake pornographic images portraying Swift were posted to X (formerly Twitter) and spread to other social media platforms, spurring criticism and demands for legal reform.[274][275] At the 66th Grammy Awards, Swift announced her eleventh studio album, The Tortured Poets Department, set for release on April 19, 2024.[248][276]
Artistry
Influences
One of Swift's earliest memories of music is listening to her maternal grandmother, Marjorie Finlay, sing in church.[5] As a child, she enjoyed Disney film soundtracks: "My parents noticed that, once I had run out of words, I would just make up my own."[277] Swift said she owes her confidence and "fascination with writing and storytelling" to her mother, who helped her prepare for class presentations as a child.[278][279]
Swift was drawn to the storytelling aspect of country music,[280] which was introduced to the genre by female country artists of the 1990s: Shania Twain, Faith Hill, and the Dixie Chicks.[281][282] Twain, both as a songwriter and performer, was her biggest musical influence.[283] Hill was Swift's childhood role model, and she would often imitate her.[284] She admired the Chicks' defiant attitude and the way they played their instruments,[285] and was also influenced by older country stars like Patsy Cline, Loretta Lynn, Tammy Wynette, and Dolly Parton,[22] the last of whom she believes is exemplary to female songwriters.[114] As a songwriter, Swift was influenced by Joni Mitchell's emotional and autobiographical lyrics, highlighting Mitchell's 1971 album Blue as a favorite "because it explores somebody's soul so deeply".[286] She also spoke of influence from 1990s songwriters such as Melissa Etheridge, Sarah McLachlan, and Alanis Morissette,[287][288] and alt-country artists like Patty Griffin[289] and Lori McKenna.[290]
Various pop and rock artists have also influenced Swift. She lists Paul McCartney, Bruce Springsteen, Emmylou Harris, and Kris Kristofferson as her career role models.[12][291] 1989 was influenced by some of her favorite 1980s pop acts, including Peter Gabriel, Annie Lennox, Phil Collins, and Madonna.[292][293] She also cited Keith Urban's musical style and Fall Out Boy's lyrics as major influences.[294][295]
Genres
"If there's one thing that Swift has proven throughout her career, it's that she refuses to be put in a box. Her ever-evolving sound took her from country darling to pop phenom to folk's newest raconteur."
—The Recording Academy, 2021[296]
Swift is known for venturing into various music genres and undergoing artistic reinventions,[297][264] having been described as a "music chameleon".[298][299] She self-identified as a country musician until 2012, when she released her fourth studio album, Red.[300] Her albums were promoted to country radio, but music critics noted wide-ranging styles of pop and rock[301][302] and said that the melodies of her songs were rooted in pop, and the country music elements were limited to instruments such as banjo, mandolin, and fiddle, and her slight twang.[303][304] Some commented that her country music identity was an indicator of her narrative songwriting rather than musical style.[305][306] Although the Nashville music industry was receptive of Swift's status as a country musician, critics accused her of abandoning her roots in favor of crossover success in mainstream pop.[307][308] Red's eclectic pop, rock, and electronic styles intensified the critical debate, to which Swift responded, "I leave the genre labeling to other people."[309]
Music journalist Jody Rosen commented that by originating her musical career in Nashville, Swift made a "bait-and-switch maneuver, planting roots in loamy country soil, then pivoting to pop".[310] She abandoned her country music identity in 2014 with the release of her synth-pop fifth studio album, 1989. Swift described it as her first "documented, official pop album".[311] Her subsequent albums Reputation (2017) and Lover (2019) have an upbeat pop production; the former incorporates hip hop, trap, and EDM elements.[312][313][314] Midnights (2022), on the other hand, is distinguished by a more experimental, "subdued and amorphous pop sound".[315][316] Although reviews of Swift's pop albums were generally positive, some critics lamented that the pop music production indicated Swift's pursuit of mainstream success, eroding her authenticity as a songwriter nurtured by her country music background—a criticism that has been retrospectively described as rockist.[317][318] Musicologist Nate Sloan remarked that Swift's pop music transition was rather motivated by her need to expand her artistry.[319] Swift eschewed mainstream pop in favor of alternative, folk and indie rock styles with her 2020 studio albums Folklore and Evermore.[320][321] Clash said her career "has always been one of transcendence and covert boundary-pushing", reaching a point at which "Taylor Swift is just Taylor Swift", not defined by any genre.[322]
Voice
"Cardigan"
Duration: 22 seconds.0:22
Swift uses her lower register in "Cardigan" (2020).[323]
"Lavender Haze"
Duration: 18 seconds.0:18
"Lavender Haze" (2022) features Swift's falsetto vocals in the refrain.[324]
Problems playing these files? See media help.
Swift possesses a mezzo-soprano vocal range,[325] and a generally soft but versatile timbre.[326][327] As a country singer, her vocals were criticized by some as weak and strained compared to those of her contemporaries.[328] Swift admitted her vocal ability often concerned her in her early career and has worked hard to improve.[329] Reviews of her vocals remained mixed after she transitioned to pop music with 1989; critics complained that she lacked proper technique but appreciated her usage of her voice to communicate her feelings to the audience, prioritizing "intimacy over power and nuance".[330] They also praised her for refraining from correcting her pitch with Auto-Tune.[331]
The Los Angeles Times remarked that Swift's defining vocal feature is her attention to detail to convey an exact feeling—"the line that slides down like a contented sigh or up like a raised eyebrow".[332] With Reputation, critics noted she was "learning how to use her voice as a percussion instrument of its own",[333] swapping her "signature" expressive vocals for "cool, conversational, detached" cadences and rhythms similar to hip hop and R&B styles.[334][335][336] Alternative Press stated that her "evocative" vocal stylings are more reminiscent of pop-punk and emo genres.[337]
Reviews of Swift's later albums and performances were more appreciative of her vocals, finding them less nasal, richer, more resonant, and more powerful.[304][338][339] With Folklore and Evermore, Swift received praise for her sharp and agile yet translucent and controlled voice.[340][341][342] Pitchfork described it as "versatile and expressive".[343] With her 2021 re-recorded albums, critics began to praise the mature, deeper and "fuller" tone of her voice.[344][345][346] An i review said Swift's voice is "leagues better now".[347] The Guardian highlighted "yo-yoing vocal yelps" and passionate climaxes as the trademarks of Swift's voice,[348] and that her country twang faded away.[349] Midnights received acclaim for Swift's nuanced vocal delivery.[350] She ranked 102nd on the 2023 Rolling Stone list of the 200 Greatest Singers of All Time.[327] In a review of the Eras Tour, The New Yorker critic Amanda Petrusich praised the clarity and tone of Swift's live vocals.[351] Musicologist Alyssa Barna said that Swift's timbre is "breathy and bright" in her upper register and "full and dark" in the lower.[222]
Songwriting
Further information: List of songs by Taylor Swift
Swift has been referred to as one of the greatest songwriters ever by several publications.[352][353][354] Literature scholars like Jonathan Bate and Stephanie Burt have noted that her literary and melodic sensibility and writing style are rare amongst her peers.[355][356] Swift's bridges are often noted as one of the best aspects of her songs,[357][358] earning her the title "Queen of Bridges" from Time.[359] Mojo described her as "a sharp narrator with a gift for the extended metaphor".[360]
In The New Yorker in 2011, Swift said she identifies as a songwriter first: "I write songs, and my voice is just a way to get those lyrics across".[12] Her personal experiences were a common inspiration for her early songs, which helped her navigate life.[361][362] Her "diaristic" technique began with identifying an emotion, followed by a corresponding melody.[363][364] On her first three studio albums, love, heartbreak, and insecurities, from an adolescent perspective, were dominant themes.[365][366] She delved into the tumult of toxic relationships on Red,[367] and embraced nostalgia and post-romance positivity on 1989.[292] Reputation was inspired by the downsides of Swift's fame,[368] and Lover detailed her realization of the "full spectrum of love".[369] Other themes in Swift's music include family dynamics, friendship,[370][371] alienation, self-awareness, and tackling vitriol, especially sexism.[279][372]
Her confessional lyrics received positive reviews from critics,[373][12][374] who highlighted their vivid details and emotional engagement, which they found uncommon in pop music.[375][376][377] Critics also praised her melodic compositions; Rolling Stone described Swift as "a songwriting savant with an intuitive gift for verse-chorus-bridge architecture".[378][379] NPR dubbed Swift "a master of the vernacular in her lyrics",[335] remarking that her songs offer emotional engagement because "the wit and clarity of her arrangements turn them from standard fare to heartfelt disclosures".[379] Despite the positive reception, The New Yorker stated she was generally portrayed "more as a skilled technician than as a Dylanesque visionary".[12] Tabloid media often speculated and linked the subjects of her songs with her ex-lovers, a practice reviewers and Swift herself criticized as sexist.[380][381][382] Aside from clues in album liner notes, Swift avoided talking about the subjects of her songs.[383]
On her 2020 albums Folklore and Evermore, Swift was inspired by escapism and romanticism to explore fictional narratives.[384] She imposed emotions onto imagined characters and story arcs, which liberated her from tabloid attention and suggested new paths for her artistry.[363] Swift explained that she welcomed the new songwriting direction after she stopped worrying about commercial success.[384] According to Spin, she explored complex emotions with "precision and devastation" on Evermore.[385] Consequence stated her 2020 albums convinced skeptics of her songwriting prowess, noting her transformation from "teenage wunderkind to a confident and careful adult".[358]
Swift divides her writing into three types: "quill lyrics", songs rooted in antiquated poeticism; "fountain pen lyrics", based on modern and vivid storylines; and "glitter gel pen lyrics", which are lively and frivolous.[386] Critics note the fifth track of every Swift album as the most "emotionally vulnerable" of the album.[387] Awarding her with the Songwriter Icon Award in 2021, the National Music Publishers' Association remarked that "no one is more influential when it comes to writing music today".[388] The Week deemed her the foremost female songwriter of modern times,[389] and the Nashville Songwriters Association International named her Songwriter-Artist of the Decade in 2022.[245] Swift has also published two original poems: "Why She Disappeared" and "If You're Anything Like Me".[390]
Performances
Further information: List of Taylor Swift live performances
Swift performing on the Reputation Stadium Tour in Seattle in May 2018
Journalists have described Swift as one of the best live performers. Often praised for her showmanship and stage presence,[391][392][393][394][395] Swift commands large audiences,[396][397][398] without having to rely on dance like her contemporaries do.[399] According to V magazine's Greg Krelenstein, she possesses "a rare gift of turning a stadium spectacle into an intimate setting", irrespective of whether she is "plucking a guitar or leading an army of dancers".[400] In a 2008 review of Swift's early performances, Sasha Frere-Jones of The New Yorker called Swift a "preternaturally skilled" entertainer with a vibrant stage presence, adding "she returned the crowd's energy with the professionalism she has shown since the age of fourteen."[401] In 2023, Adrian Horton of The Guardian noted her "seemingly endless stamina" on the Eras Tour,[402] and i critic Ilana Kaplan called her showmanship "unparalleled".[403]
Critics have highlighted Swift's versatility as an entertainer, praising her ability to switch onstage personas and performance styles depending on the varying themes and aesthetics of her albums.[404][405] Her concert productions have been characterized by elaborate Broadway theatricality and high technology,[406] and her performances frequently incorporate a live band, with whom she has played and toured since 2007.[407] Swift also often accompanies herself with musical instruments such as electric guitar;[408] acoustic guitar; piano;[409] and sometimes twelve-string guitar,[410][411] banjo,[412] or ukulele.[413] Interacting frequently with the audience, her solo acoustic performances are considered intimate and emotionally resonant, complementing her story-based lyrics and fan connection.[351][414] Lydia Burgham of The Spinoff opined that this intimacy remains "integral to her singer-songwriter origins".[415][409] Chris Willman of Variety called Swift "pop's most approachable superstar",[416] and the 21st century's most popular performer.[417]
Video and film
Further information: Taylor Swift videography
Swift emphasizes visuals as a key creative component of her music-making process.[418] She has collaborated with different directors to produce her music videos, and over time she has become more involved with writing and directing. She developed the concept and treatment for "Mean" in 2011[419] and co-directed the music video for "Mine" with Roman White the year before.[420] In an interview, White said that Swift "was keenly involved in writing the treatment, casting and wardrobe. And she stayed for both the 15-hour shooting days, even when she wasn't in the scenes."[421]
From 2014 to 2018, Swift collaborated with director Joseph Kahn on eight music videos—four each from her albums 1989 and Reputation. Kahn has praised Swift's involvement.[422] She worked with American Express for the "Blank Space" music video (which Kahn directed), and served as an executive producer for the interactive app AMEX Unstaged: Taylor Swift Experience, for which she won a Primetime Emmy Award for Outstanding Interactive Program in 2015.[423] Swift produced the music video for "Bad Blood" and won a Grammy Award for Best Music Video in 2016.[424]
Her production company, Taylor Swift Productions, is credited with producing all of her visual media starting with the 2018 concert documentary Reputation Stadium Tour.[425] She continued to co-direct music videos for the Lover singles "Me!" with Dave Meyers, and "You Need to Calm Down" (also serving as a co-executive producer) and "Lover" with Drew Kirsch,[426] but first ventured into sole direction with the video for "The Man" (which won her the MTV Video Music Award for Best Direction).[427] After Folklore: The Long Pond Studio Sessions, Swift debuted as a filmmaker with All Too Well: The Short Film,[245] which made her the first artist to win the Grammy Award for Best Music Video as a sole director.[428] Swift has cited Chloé Zhao, Greta Gerwig, Nora Ephron, Guillermo del Toro, John Cassavetes, and Noah Baumbach as filmmaking influences.[418]
Accolades and achievements
Further information: List of awards and nominations received by Taylor Swift
In 2009, Swift became the first country singer to win an MTV Video Music Award.
Swift's discography is a "critically hailed songbook", as per Time's Sam Lansky.[429] She has won 14 Grammy Awards (including four for Album of the Year—the most won by an artist),[430] an Emmy Award,[431] 40 American Music Awards (the most won by an artist),[432] 39 Billboard Music Awards (the most won by an artist—tying with Drake),[433] 118 Guinness World Records,[434] 23 MTV Video Music Awards (including four Video of the Year wins—the most by an act),[247] 12 Country Music Association Awards (including the Pinnacle Award),[435] eight Academy of Country Music Awards,[436] and two Brit Awards.[168] As a songwriter, she has been honored by the Nashville Songwriters Association,[63][437] the Songwriters Hall of Fame, and the National Music Publishers' Association and was the youngest person on Rolling Stone's list of the 100 Greatest Songwriters of All Time in 2015.[438][439] At the 64th BMI Awards in 2016, Swift was the first woman to be honored with an award named after its recipient.[440]
Commercially, from available data, Swift has amassed over 50 million album sales and 150 million single sales as of 2019,[441][442][443] and 114 million units globally, including 78 billion streams as of 2021.[444][445] The International Federation of the Phonographic Industry ranked her as the Global Recording Artist of the Year for a record three times (2014, 2019 and 2022).[446] Swift has the most number-one albums in the United Kingdom and Ireland for a female artist this millennium,[447][448] earned the highest income for an artist on Chinese digital music platforms (RMB 159,000,000 as of 2021),[449] and is the first artist to replace themselves at the top spot and occupy the entire top five[note 3] of the Australian albums chart.[452][453] Swift remains the world's highest-grossing female touring act ever, with cumulative ticket sales at $1.96 billion as of November 2023 according to Pollstar.[454] The Eras Tour is the highest-grossing tour of all time as of December 2023, and the first to surpass $1 billion in revenue.[455] Beginning with Fearless, each of her studio albums have opened with over one million global units.[456][457] Swift is the most streamed female act on Spotify and Apple Music.[458][459] On Spotify, she is the only artist to have received more than 200 and 250 million streams in one day (260 million on October 27, 2023),[460] and the only female act to reach 100 million monthly listeners.[234] The most entries and the most simultaneous entries for an artist on the Billboard Global 200, with 143 and 31 songs, respectively, are among her feats.[461][462]
In the US, Swift has sold over 37.3 million albums as of 2019,[443] when Billboard placed her eighth on its Greatest of All Time Artists Chart.[463] Eleven of her songs have topped the Billboard Hot 100.[257] She is the longest-reigning act of the Billboard Artist 100 (97 weeks);[464] the soloist with the most cumulative weeks atop the Billboard 200 (68);[465] the woman with the most Billboard 200 number-ones (13),[234] Hot 100 entries (232),[234][156] number-one debuts (6),[note 4] top-ten songs (49),[257] and weeks atop the Top Country Albums chart (101);[467] and the act with the most number-one songs on Pop Airplay (12) and Digital Songs (28).[468][469] Swift is the first woman to simultaneously chart five albums in the top 10 and eleven albums on the entire Billboard 200;[470][471] and the first act to occupy the top four spots and chart seven albums[note 5] in the top 10 on the Top Album Sales chart.[473][474] She is the second highest-certified female digital singles artist (and fifth overall) in the US, with 137.5 million total units certified by the Recording Industry Association of America (RIAA),[475] and the first woman to have both an album (Fearless) and a song ("Shake It Off") certified Diamond.[476] Swift is the only artist in Luminate history to have six albums sell over a million copies in a week.[477]
Swift has appeared in various power listings. Time included her on its annual list of the 100 most influential people in 2010, 2015, and 2019.[478] She was one of the "Silence Breakers" that the magazine spotlighted as Person of the Year in 2017 for speaking up about sexual assault,[479] and received the honor again in 2023 for her cultural domination that year.[429] Time described Swift as the first Person of the Year to be recognized for "achievement in the arts", as well as the first woman to be recognized and appear on a Person of the Year cover more than once.[480][481] In 2014, she was named to Forbes' 30 Under 30 list in the music category[482] and again in 2017 in its "All-Star Alumni" category.[483] Swift became the youngest woman to be included on Forbes' list of the 100 most powerful women in 2015, ranked at number 64.[484] In 2023, she was ranked by Forbes as the fifth-most powerful woman in the world, the first entertainer to place in the top five.[485] Swift received an honorary Doctor of Fine Arts degree from New York University and served as its commencement speaker on May 18, 2022.[245]
Cultural status
Main articles: Cultural impact of Taylor Swift and Public image of Taylor Swift
Swift at the 2010 Time 100 Gala
Swift has been credited with making a profound impact on the music industry, popular culture and the economy.[486][487] She dominates cultural conversations,[488][489] which has led publications to describe her as a cultural "vitality" or zeitgeist.[490][491][492] Her music, life and public image are points of attention in global celebrity culture.[297] Initially a teen idol,[493] she has been referred to as a pop icon;[312][494] publications describe her immense popularity and longevity as unwitnessed since the 20th century.[495][496] In 2013, New York magazine's Jody Rosen dubbed Swift the "world's biggest pop star" and opined that the trajectory of her stardom has defied established patterns. Rosen added that Swift "falls between genres, eras, demographics, paradigms, trends", leaving her contemporaries "vying for second place".[310] Critics regard Swift as a rare yet successful combination of the pop star and singer-songwriter archetypes.[497]
Her fans are known as Swifties.[266] Billboard noted only few artists have had her chart success, critical acclaim, and fan support.[498] Swift's million-selling albums are considered an anomaly in the streaming-dominated industry following the end of the album era in the 2010s.[499][500] Economist Alan Krueger described Swift as an "economic genius".[501]
Although labeled by the media in her early career as "America's Sweetheart" for her girl next door persona,[502][503] Swift has been accused by detractors of being "calculated" and manipulative of her image, a narrative bolstered by her 2016 dispute with West.[173][174] Critics have also noted that her personal life and career have been subject to intense misogyny and "slut-shaming",[504][505] as well as rampant media scrutiny and tabloid speculation.[506]
Swift's private jet use has drawn scrutiny for its carbon emissions.[507][508] In 2023, a spokesperson for Swift stated that she had purchased more than double the required carbon credits to offset all tour travel and personal flights.[509][510] In December 2023, Swift's lawyers sent a cease and desist letter to American programmer Jack Sweeney over tracking her private jet, citing safety concerns and stalking.[511][512] Swift has been a victim of numerous house break-ins and stalkers, some of whom were armed.[513][514]
Legacy
"You have different artists dominating different sectors of the industry: Some are huge at streaming, some are big draws on the road. But we're at this moment where there's no one better than Taylor Swift, whether that's on the radio, with streaming, ticket sales or just cultural impact."
– Jason Lipshutz, Billboard executive director, 2023[515]
Swift helped shape the modern country music scene,[516] having extended her success beyond the Anglosphere,[310][516] pioneered the use of internet (Myspace) as a marketing tool,[33][53] and introduced the genre to a younger generation.[517][310] Country labels have since become interested in signing young singers who write their own music;[518] her guitar performances contributed to the "Taylor Swift factor", a phenomenon to which an upsurge in guitar sales to women, a previously ignored demographic, is attributed.[519][520]
According to publications, Swift changed the music landscape with her genre transitions, a discography that accommodates cultural shifts,[521] and her ability to popularize any sound in mainstream music.[522] Lyrically, in being personal and vulnerable in her songs, music journalist Nick Catucci opined Swift helped make space for later singers like Billie Eilish, Ariana Grande, and Halsey to do the same.[523] Scholars have highlighted the literary sensibility and poptimist implications of Swift.[355][524] She has been credited with legitimizing and popularizing the concept of album "eras".[525][526] Swift is a subject of academic study and scholarly media research.[297] Various educational institutions offer courses on Swift in literary, cultural and sociopolitical contexts.[527][297]
Swift has influenced numerous music artists, and her albums have inspired a generation of singer-songwriters.[517][320][528] Journalists praise her ability to reform industry practices, noting how her actions changed streaming policies, prompted awareness of intellectual property in new musicians,[529][530] and reshaped ticketing models.[531] Various sources deem Swift's music a paradigm representing the millennial generation;[532] Vox called her the "millennial Bruce Springsteen",[533] and The Times named her "the Bob Dylan of our age".[534] Swift earned the title Woman of the Decade (2010s) from Billboard,[535] Artist of the Decade (2010s) at the American Music Awards,[536] and Global Icon at the Brit Awards for her impact.[445] Senior artists such as Paul McCartney,[537] Mick Jagger,[538] Madonna,[539] and Dolly Parton have praised her musicianship.[540] Carole King regards Swift her "professional grand daughter" and thanked Swift for "carrying the torch forward".[541] Springsteen called her a "tremendous" writer,[542] while Ringo Starr and Billy Joel considered Swift the Beatles' successor.[543][544] Britney Spears labeled Swift "the most iconic pop woman of our generation".[545]
Entrepreneurship
Media outlets describe Swift as a savvy businesswoman;[546][547] in 2024, she topped Billboard's annual Power 100 ranking of the top music industry executives.[548] Swift is known for her traditional album rollouts, consisting of a variety of promotional activities that Rolling Stone termed as an inescapable "multimedia bonanza".[549][550] Easter eggs and cryptic teasers became a common practice in contemporary pop music because of Swift.[551] Publications describe her discography as a music "universe" subject to analyses by fans, critics and journalists.[552][553][554] Swift maintains an active presence on social media and a close relationship with fans, to which many journalists attribute her success.[555][487][556] Her in-house management team is called 13 Management.[557]
Swift has endorsed many brands and businesses, having launched clothing lines with L.E.I. and Stella McCartney,[558][559] designed American Greetings cards and Jakks Pacific dolls,[560][561] released a number of fragrances with Elizabeth Arden,[562] and signed multi-year deals with AT&T and Capital One.[563][564] She was a spokesperson for the National Hockey League's Nashville Predators and Sony Cyber-shot digital cameras,[565][566] and became the global ambassador for New York City in 2014 and Record Store Day in 2022.[567][568]
Social activism
Further information: Political impact of Taylor Swift
Swift identifies as a pro-choice feminist,[569] and is a founding signatory of the Time's Up movement against sexual harassment.[570] Specifically, she criticized the US Supreme Court's decision to end federal abortion rights in 2022.[571] Swift also advocates for LGBT rights,[572] and has called for the passing of the Equality Act, which prohibits discrimination based on sex, sexual orientation, and gender identity.[573][574] She performed during WorldPride NYC 2019 at the Stonewall Inn, a gay rights monument, and has donated to the LGBT organizations Tennessee Equality Project and GLAAD.[575][576][577]
A supporter of the March for Our Lives movement and gun control reform in the US,[578] Swift is a vocal critic of white supremacy, racism, and police brutality.[579][569] Following the George Floyd protests, she donated to the NAACP Legal Defense and Educational Fund and the Black Lives Matter movement,[580] called for the removal of Confederate monuments in Tennessee,[581] and advocated for Juneteenth to become a national holiday.[582] In 2020, Swift urged her fans to check their voter registration ahead of elections, which resulted in 65,000 people registering to vote within one day of her post,[583] and endorsed Joe Biden and Kamala Harris in the US presidential election.[584] She has openly criticized former president Donald Trump.[585]
Wealth
Swift's net worth is estimated by Forbes and Bloomberg News at $1.1 billion as of October 2023, making her the first musician to achieve billionaire status "solely based on her songs and performances".[586][587] Forbes named her the annual top-earning female musician in 2016, 2019, 2021, and 2022.[588] She was the highest-paid celebrity of 2016 with $170 million—a feat recognized by the Guinness World Records as the highest annual earnings ever for a female musician,[589] which she herself surpassed with $185 million in 2019.[590] Overall, Forbes listed Swift as the highest-paid female artist of the 2010s, earning $825 million.[591] She has also developed a real estate portfolio worth $150 million as of 2023, with properties in Nashville; Tribeca, Manhattan; Los Angeles (Samuel Goldwyn Estate); and Rhode Island (High Watch).[592]
Philanthropy
Swift is known for her philanthropic efforts.[593] She ranked first on DoSomething's 2015 "Gone Good" list,[594] having received the Star of Compassion from the Tennessee Disaster Services and the Big Help Award from the Nickelodeon Kids' Choice Awards for her "dedication to helping others" and "inspiring others through action".[595][596] She donated $100,000 to the Red Cross to help the victims of the Iowa flood of 2008.[597] In 2009, she sang at BBC's Children in Need concert and raised £13,000 for the cause.[598] Swift has performed at charity relief events, including Sydney's Sound Relief concert.[599] In response to the May 2010 Tennessee floods, Swift donated $500,000.[600] In 2011, Swift used a dress rehearsal of her Speak Now tour as a benefit concert for victims of recent tornadoes in the US, raising more than $750,000.[601] In 2016, she donated $1 million to Louisiana flood relief efforts and $100,000 to the Dolly Parton Fire Fund.[602][603] Swift donated to food banks after Hurricane Harvey struck Houston in 2017 and at every stop of the Eras Tour in 2023;[604][605] she also directly employed local businesses throughout the tour and gave $55 million in bonus payments to her entire crew.[606][607] Swift donated $1 million for Tennessee tornado relief in 2020 and again in 2023.[608][609]
She is a supporter of the arts. A benefactor of the Nashville Songwriters Hall of Fame,[610] Swift has donated $75,000 to Nashville's Hendersonville High School to help refurbish the school auditorium,[611] $4 million to build a new education center at the Country Music Hall of Fame and Museum in Nashville,[612] $60,000 to the music departments of six US colleges,[613] and $100,000 to the Nashville Symphony.[614] Also a promoter of children's literacy, she has donated money and books to schools around the country.[615][616] In 2007, Swift partnered with the Tennessee Association of Chiefs of Police to launch a campaign to protect children from online predators.[617] She has donated items to several charities for auction, including the UNICEF Tap Project and MusiCares.[618] As recipient of the Academy of Country Music's Entertainer of the Year in 2011, Swift donated $25,000 to St. Jude Children's Research Hospital, Tennessee.[619] In 2012, Swift participated in the Stand Up to Cancer telethon, performing the charity single "Ronan", which she wrote in memory of a four-year-old boy who died of neuroblastoma.[620] She has also donated $100,000 to the V Foundation for Cancer Research[621] and $50,000 to the Children's Hospital of Philadelphia.[622] Swift has encouraged young people to volunteer in their local communities as part of Global Youth Service Day.[623]
Swift donated to fellow singer-songwriter Kesha to help with her legal battles against Dr. Luke and to actress Mariska Hargitay's Joyful Heart Foundation.[593][624] During the COVID-19 pandemic, Swift donated to the World Health Organization and Feeding America,[625] and supported independent record stores.[626][627] Swift performed "Soon You'll Get Better" on the One World: Together At Home television special, a benefit concert curated by Lady Gaga for Global Citizen to raise funds for the World Health Organization's COVID-19 Solidarity Response Fund.[628] In 2018 and 2021, Swift donated to the Rape, Abuse & Incest National Network in honor of Sexual Assault Awareness and Prevention Month.[593][629] She has made donations to her fans several times for their medical or academic expenses.[630] In December 2023, Swift attended Ramy Youssef's fundraiser for the Gaza Strip.[631]
Discography
Main articles: Taylor Swift albums discography, Taylor Swift singles discography, and List of songs by Taylor Swift
Studio albums
Taylor Swift (2006)
Fearless (2008)
Speak Now (2010)
Red (2012)
1989 (2014)
Reputation (2017)
Lover (2019)
Folklore (2020)
Evermore (2020)
Midnights (2022)
The Tortured Poets Department (2024)
Re-recorded albums
Fearless (Taylor's Version) (2021)
Red (Taylor's Version) (2021)
Speak Now (Taylor's Version) (2023)
1989 (Taylor's Version) (2023)
Filmography
Main article: Taylor Swift videography
This section lists select works only. Refer to the main article for further information.
Valentine's Day (2010)
The Lorax (2012)
The Giver (2014)
Cats (2019)
All Too Well: The Short Film (also director) (2021)
Amsterdam (2022)
Documentary and concert films
Journey to Fearless (2010)
Speak Now World Tour – Live (2011)
The 1989 World Tour Live (2015)
Taylor Swift: Reputation Stadium Tour (2018)
Miss Americana (2020)
Taylor Swift: City of Lover (2020)
Folklore: The Long Pond Studio Sessions (also director) (2020)
Taylor Swift: The Eras Tour (2023)
Tours
Main article: List of Taylor Swift live performances
Fearless Tour (2009–2010)
Speak Now World Tour (2011–2012)
The Red Tour (2013–2014)
The 1989 World Tour (2015)
Reputation Stadium Tour (2018)
The Eras Tour (2023–2024)
See also
List of American Grammy Award winners and nominees
List of highest-certified music artists in the United States
List of most-followed Instagram accounts
List of most-followed Twitter accounts
List of most-subscribed YouTube channels
Footnotes
Swift held the record until the 62nd Annual Grammy Awards in 2020.[91][92]
Though Swift has properties throughout the US, she identifies Nashville as her home.[149][150]
Swift has occupied the top five of the ARIA Albums Chart twice. She achieved this feat first on the issue published on July 7, 2023,[450] followed by a second time on the issue published on February 9, 2024.[451]
In a tie with Ariana Grande.[466]
Swift has charted seven titles in the top 10 of the Top Album Sales chart twice—on the issues dated January 6, 2024, and January 20, 2024.[472]
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Chart positions:
• "Taylor Swift – I Knew You Were Trouble". ARIA Charts. Archived from the original on May 27, 2016. Retrieved February 14, 2021.
• "Official Singles Charts Top 100". Official Charts Company. Archived from the original on July 13, 2021. Retrieved February 14, 2021.
• "Taylor Swift Leads Record Breaking Digital Sales Week". Billboard. January 3, 2013. Archived from the original on April 8, 2017. Retrieved February 14, 2021.
Lewis, Randy (October 30, 2012). "Taylor Swift raises the bar with a savvy 'Red' marketing campaign". Los Angeles Times. Archived from the original on December 28, 2020. Retrieved December 28, 2020.
Mansfield, Brian (October 17, 2012). "Taylor Swift sees 'Red' all over". USA Today. Archived from the original on December 21, 2012.
English, J. (August 28, 2017). "Taylor Swift's 'Red': A Canonical Coming-Of-Age Album". NPR. Archived from the original on April 12, 2021. Retrieved February 14, 2021.
Roberts, Randall (October 31, 2012). "'The Last Time' connects Taylor Swift with Arcade Fire". Los Angeles Times. Archived from the original on March 6, 2016. Retrieved December 27, 2020.
Greenwald, David (September 6, 2013). "Taylor Swift, Rihanna, Justin Bieber Among 2014 Guinness Record-Setters". Billboard. Archived from the original on June 8, 2015. Retrieved July 27, 2016.
Sexton, Paul (August 31, 2019). "Taylor Swift Scores Fourth U.K. No. 1 With 'Lover' Album". Billboard. Archived from the original on August 16, 2021. Retrieved October 15, 2019.
"Grammys 2014: The complete list of nominees and winners". Los Angeles Times. January 26, 2014. Archived from the original on March 4, 2015. Retrieved January 25, 2015.
Gregoire, Carolyn (November 19, 2012). "Taylor Swift AMA Awards 2012: Pop Star Performs 'I Knew You Were Trouble' (Video)". HuffPost. Archived from the original on May 26, 2013. Retrieved June 10, 2013.
Payne, Chris (November 25, 2013). "Taylor Swift & Justin Timberlake Win Big at American Music Awards". Billboard. Archived from the original on November 24, 2015. Retrieved November 21, 2015.
"NSAI Songwriter/Artists of the Year". Nashville Songwriters Association International. Archived from the original on August 19, 2016. Retrieved August 2, 2016.
Allen, Bob (July 3, 2014). "Taylor Swift's Red Wraps as All-Time Country Tour". Billboard. Archived from the original on June 1, 2015. Retrieved April 11, 2015.
Caramanica, Jon (November 7, 2013). "Country Awards Hold Swift Close". The New York Times. Archived from the original on November 11, 2013. Retrieved April 3, 2014.
"Taylor Swift's Boyfriend Timeline: 10 Relationships & Their Songs". Billboard. December 30, 2014. Archived from the original on August 26, 2016. Retrieved August 26, 2016.
Labrecque, Jeff (December 12, 2013). "'12 Years a Slave' and 'American Hustle' lead Golden Globe nominees". Entertainment Weekly. Archived from the original on March 23, 2015. Retrieved December 12, 2013.
Bonaguro, Alison (January 25, 2013). "News : Offstage: Tim McGraw Wanted to Make Taylor Swift Duet an Event". CMT. Archived from the original on July 12, 2015. Retrieved February 25, 2013.
Blistein, Doyle (June 4, 2013). "Taylor Swift Joins Rolling Stones for 'As Tears Go By'". Rolling Stone. Archived from the original on June 9, 2013. Retrieved June 10, 2013.
"Taylor Swift Joins Florida Georgia Line Onstage for 'Cruise'". Taste of Country. Townsquare Media. March 2, 2013. Archived from the original on March 16, 2013. Retrieved March 29, 2013.
Collin, Robbie (July 26, 2012). "The Lorax, review". The Daily Telegraph. Archived from the original on September 17, 2016. Retrieved August 3, 2016.
Beard, Lanford (May 1, 2013). "Taylor Swift says 'I do' to 'New Girl'". Entertainment Weekly. Archived from the original on November 8, 2016. Retrieved August 4, 2016.
Busis, Hillary (September 27, 2013). "Taylor Swift will co-star in long-awaited adaptation of 'The Giver'". Entertainment Weekly. Archived from the original on December 21, 2016. Retrieved August 2, 2016.
Peterson, Price (March 31, 2014). "Taylor Swift Moves into NYC Apartment Built Over Mysterious River of Pink Slime". The Atlantic. Archived from the original on September 27, 2016. Retrieved July 31, 2016.
Rogers, Alex (March 7, 2014). "Why Taylor Swift Thinks Nashville Is the Best Place on Earth". Time. Archived from the original on May 24, 2022. Retrieved September 27, 2016.
Milzoff, Rebecca; Brown, Eric Renner; Denis, Kyle (August 24, 2023). "Taylor Swift and Beyoncé Are So Big, Even Their Publicists Have Fans". Billboard. Archived from the original on August 24, 2023. Retrieved August 24, 2023.
Zollo, Paul (February 17, 2016). "The Oral History of Taylor Swift's 1989". The Recording Academy. Archived from the original on June 3, 2021. Retrieved February 14, 2021.
Stutz, Colin (October 16, 2014). "Watch Taylor Swift's '1989' Secret Sessions Behind The Scenes Video". Billboard. Archived from the original on June 5, 2016. Retrieved August 2, 2016.
Caulfield, Keith (November 4, 2014). "Taylor Swift's "1989" debuts with 1.287 million copies sold". Billboard. Archived from the original on November 5, 2014. Retrieved November 4, 2014.
Chart positions:
• "Discography Taylor Swift". ARIA Charts. Archived from the original on August 26, 2019. Retrieved February 14, 2021.
• "Taylor Swift Chart History (Canadian Hot 100)". Billboard. Archived from the original on August 9, 2016. Retrieved February 14, 2021.
• "Taylor Swift's 'Bad Blood' Blasts to No. 1 on Hot 100". Billboard. May 28, 2015. Archived from the original on September 6, 2015. Retrieved May 28, 2015.
"Taylor Swift – Chart History: Hot 100". Billboard. Archived from the original on March 8, 2018. Retrieved September 18, 2016.
"Live Music's $20 Billion Year: The Grateful Dead's Fare Thee Well Reunion, Taylor Swift, One Direction Top Boxscore's Year-End". Billboard. Archived from the original on December 14, 2015.
Weissmann, Jordan (July 7, 2014). "Taylor Swift Has Written an Op-Ed in the Wall Street Journal". Slate (Blog). Archived from the original on January 23, 2015. Retrieved January 23, 2015.
Knopper, Steve (November 8, 2014). "Taylor Swift's Label Head Explains Spotify Removal". Rolling Stone. Archived from the original on April 21, 2015. Retrieved April 11, 2015.
Peters, Mitchell (June 21, 2015). "Taylor Swift Pens Open Letter Explaining Why '1989' Won't Be on Apple Music". Billboard. Archived from the original on June 22, 2015. Retrieved June 22, 2015.
Halperin, Shirley (June 21, 2015). "Apple Changes Course After Taylor Swift Open Letter: Will Pay Labels During Free Trial". Billboard. Archived from the original on June 22, 2015. Retrieved June 22, 2015.
Rosen, Christopher (June 25, 2015). "Taylor Swift is putting 1989 on Apple Music". Entertainment Weekly. Archived from the original on June 26, 2015. Retrieved June 25, 2015.
"Taylor Swift returns to Spotify on the day Katy Perry's album comes out". BBC News. June 9, 2017. Archived from the original on June 9, 2017.
"Taylor Swift: 2014 Billboard Woman of the Year". Billboard. October 10, 2014. Archived from the original on June 1, 2015. Retrieved April 11, 2015.
Payne, Chris (November 23, 2014). "Taylor Swift Wins Dick Clark Award of Excellence at 2014, Presented by Diana Ross". Billboard. Archived from the original on July 4, 2015. Retrieved April 11, 2015.
"The Taylor Swift Experience". GRAMMY Museum. Archived from the original on November 25, 2022. Retrieved April 22, 2022.
Boehrer, Kat (January 7, 2016). "Watch Taylor Swift's Stunning Acoustic Performance of 'Blank Space' at the Grammy Museum". Complex. Archived from the original on April 22, 2022. Retrieved April 22, 2022.
Jonze, Tim (February 25, 2015). "Taylor Swift wins international female solo artist at Brit awards 2015". The Guardian. Archived from the original on January 1, 2016. Retrieved April 11, 2015.
Stutz, Colin (July 21, 2015). "2015 MTV Video Music Awards Nominees Revealed: Taylor Swift, Kendrick Lamar, Ed Sheeran & More". Billboard. Archived from the original on July 24, 2015. Retrieved August 15, 2016.
Lynch, Joe (February 19, 2016). "Taylor Swift Joins Elite Club to Win Grammy Album of the Year More Than Once: See the Rest". Billboard. Archived from the original on March 1, 2016. Retrieved July 31, 2016.
Chiu, Melody (June 1, 2016). "Taylor Swift and Calvin Harris Split After 15 Months Together". People. Archived from the original on June 22, 2016. Retrieved June 1, 2016.
Spanos, Brittany (July 13, 2016). "Taylor Swift Co-Wrote Calvin Harris' Smash Hit 'This Is What You Came For'". Rolling Stone. Archived from the original on July 30, 2016. Retrieved July 31, 2016.
Grady, Constance (August 26, 2019). "How the Taylor Swift-Kanye West VMAs scandal became a perfect American morality tale". Vox. Archived from the original on December 2, 2022. Retrieved October 12, 2023.
Grady, Constance (March 21, 2020). "Newly leaked footage shows Taylor Swift and Kanye West talking "Famous"". Vox. Archived from the original on March 24, 2022. Retrieved October 12, 2023.
Lewis, Anna (July 15, 2016). "Tom Hiddleston finally tells us the truth about his relationship with Taylor Swift". Cosmopolitan. Archived from the original on July 17, 2016. Retrieved January 8, 2019.
"Taylor Swift Finally Reveals When She Started Dating Joe Alwyn in Lover Album". Yahoo!. August 23, 2019. Archived from the original on June 11, 2020. Retrieved June 11, 2020.
"Paul McCartney & Taylor Swift". Rolling Stone. November 13, 2020. Archived from the original on November 30, 2020. Retrieved September 15, 2021. McCartney: So how does that go? Does your partner sympathize with that and understand? Swift: Oh, absolutely.
Irvin, Jack (April 10, 2023). "Inside Taylor Swift and Joe Alwyn's 'Differences' That Led to Their Breakup: Sources (Exclusive)". People. Archived from the original on September 25, 2023. Retrieved September 25, 2023.
"Taylor Swift, pop princess, wins song of the year at the CMA Awards". USA Today. Archived from the original on November 9, 2017. Retrieved November 9, 2017.
Trust, Gary (February 21, 2017). "Ed Sheeran Tops Hot 100, Katy Perry Debuts at No. 4 & Bruno Mars, Rihanna & The Weeknd All Hit Top 10". Billboard. Archived from the original on February 22, 2017. Retrieved February 22, 2017.
Grady, Constance (August 11, 2017). "Taylor Swift won her day in court. Here's what you need to know". Vox. Archived from the original on October 17, 2022. Retrieved October 4, 2023.
"Taylor Swift wipes social media profiles, fuelling expectations of new album". The Daily Telegraph. August 18, 2017. Archived from the original on January 8, 2019. Retrieved August 19, 2019.
Aswad, Jem (August 24, 2017). "Taylor Swift's New Single, 'Look What You Made Me Do,' Arrives (Listen)". Variety. Archived from the original on August 28, 2017. Retrieved August 29, 2017.
White, Jack (September 1, 2017). "Taylor Swift scores first Number 1 on the Official Singles Chart with 'LWYMMD'". Official Charts Company. Archived from the original on September 2, 2017. Retrieved September 1, 2017.
Peak positions:
• "Taylor Swift Scores Fifth No. 1 Single". Australian Recording Industry Association. September 2, 2017. Archived from the original on September 2, 2017. Retrieved September 2, 2017.
• "IRMA – Irish Charts". Irish Recorded Music Association. Archived from the original on June 14, 2017. Retrieved September 2, 2017.
• "NZ Top 40 Singles Chart". Recorded Music NZ. September 4, 2017. Archived from the original on September 1, 2017. Retrieved September 1, 2017.
• "Taylor Swift at Nos. 1 & 4 on Billboard Hot 100, as Cardi B Moves Up to No. 2". Billboard. September 11, 2017. Archived from the original on September 21, 2017. Retrieved October 30, 2017.
Shaw, Lucas (November 7, 2017). "Taylor Swift Will Keep New Album From Streaming for a Week". Bloomberg. Bloomberg News. Archived from the original on November 8, 2017. Retrieved November 7, 2017.
Powers, Ann (November 10, 2019). "The Old Taylor's Not Dead". NPR. Archived from the original on June 9, 2020. Retrieved June 29, 2020.
McDermott, Maeve (October 11, 2017). "Taylor Swift 'Reputation': Here's what critics are saying". USA Today. Archived from the original on March 4, 2020. Retrieved October 15, 2020.
"Official: Taylor Swift's 'Reputation' Album Sells 1.2M Copies in US During First Week". Billboard. Archived from the original on November 30, 2017. Retrieved May 29, 2018.
Chart positions:
• "Taylor Swift's 'Reputation' Rules Australia's Albums Chart". Billboard. November 20, 2017. Archived from the original on November 20, 2017. Retrieved December 2, 2017.
• "Taylor Swift Chart History". Billboard. Archived from the original on November 22, 2021. Retrieved November 19, 2021.
Unterberger, Andrew (July 6, 2018). "Taylor Swift's 'Delicate' Became the Biggest Reputation Radio Hit While You Weren't Looking". Billboard. Archived from the original on December 13, 2020. Retrieved April 13, 2020.
"61st Grammy Nominees". The Recording Academy. December 7, 2018. Archived from the original on December 7, 2018. Retrieved December 7, 2018.
Hudak, Joseph (April 12, 2018). "Sugarland Announce New Album Bigger, Taylor Swift Collaboration". Rolling Stone. Archived from the original on April 14, 2018. Retrieved April 13, 2018.
Havens, Lyndsey (October 9, 2018). "Taylor Swift Breaks an All-Time AMA Record – And Urges People to Vote in Midterm Elections". Billboard. Archived from the original on October 10, 2018. Retrieved October 10, 2018.
Stubblebine, Allison (November 13, 2017). "Taylor Swift Announces First Round of Reputation Stadium Tour Dates". Billboard. Archived from the original on November 14, 2017. Retrieved November 18, 2017.
Frankenberg, Eric (December 6, 2018). "Taylor Swift Closes Reputation Stadium Tour with $345 Million". Billboard. Archived from the original on December 9, 2018. Retrieved December 22, 2018.
Wang, Amy X. (November 19, 2018). "Taylor Swift's New Record Deal Affects Thousands of Other Musicians". Rolling Stone. Archived from the original on November 26, 2018. Retrieved November 26, 2018.
Willman, Chris (August 27, 2018). "Taylor Swift Stands to Make Music Business History as a Free Agent". Variety. Archived from the original on August 29, 2018. Retrieved August 29, 2018.
Aswad, Jem; Willman, Chris (November 19, 2018). "Taylor Swift Signs New Deal With Universal Music Group". Variety. Archived from the original on November 19, 2018. Retrieved November 19, 2018.
Grady, Constance (November 19, 2018). "What Taylor Swift's new record deal means for the music industry — and for her image". Vox. Archived from the original on December 20, 2021. Retrieved December 20, 2021.
McKenna, Lyndsey (August 23, 2019). "Stream Taylor Swift's New Album, 'Lover'". NPR. Archived from the original on February 19, 2020. Retrieved September 10, 2019.
Catucci, Nick (August 23, 2019). "Taylor Swift Reaches For New Heights of Personal and Musical Liberation on 'Lover'". Rolling Stone. Archived from the original on August 23, 2019. Retrieved February 15, 2021.
Caulfield, Keith (September 1, 2019). "Official: Taylor Swift's 'Lover' Debuts at No. 1 on Billboard 200 Chart With 867,000 Units Earned in First Week in U.S." Billboard. Archived from the original on September 1, 2019. Retrieved September 2, 2019.
White, Adam (August 23, 2019). "Taylor Swift Lover Review Round-Up: Critics Say Album Feels 'Evolutionary Rather Than Revolutionary'". The Independent. Archived from the original on June 13, 2022. Retrieved June 13, 2022.
Moniuszko, Sara M. (August 23, 2019). "Taylor Swift Lover Reviews: Critics Are Enamored by the 'Earnest,' 'Romantic' New Album". USA Today. Archived from the original on August 23, 2019. Retrieved November 5, 2020.
Trust, Gary (May 6, 2019). "Lil Nas X's 'Old Town Road' Tops Billboard Hot 100 For Fifth Week, Taylor Swift's 'Me!' Vaults to No. 2". Billboard. Archived from the original on May 6, 2019. Retrieved June 14, 2019.
Trust, Gary (October 23, 2023). "Taylor Swift's 'Cruel Summer' Hits No. 1 on Billboard Hot 100, Becoming Her 10th Leader". Billboard. Archived from the original on October 24, 2023. Retrieved October 24, 2023.
"Arashi Best-Of Tops Taylor Swift for IFPI's Best-Selling Album of 2019". Billboard. March 19, 2020. Archived from the original on March 19, 2020. Retrieved March 21, 2020.
"2020 Grammy Awards: Complete Winners List". The Recording Academy. November 20, 2019. Archived from the original on May 22, 2020. Retrieved February 15, 2021.
Grein, Paul (August 26, 2019). "12 Records That Were Set at the 2019 VMAs". Billboard. Archived from the original on January 30, 2020. Retrieved January 11, 2020.
Grady, Constance (September 1, 2019). "The Taylor Swift/Scooter Braun controversy, explained". Vox. Archived from the original on February 11, 2020. Retrieved August 23, 2019.
Beth, John (January 2, 2024). "Taylor Swift's Chart Triumph". Square News.
"The Taylor Swift, Scooter Braun, Justin Bieber row explained". BBC News. July 1, 2019. Archived from the original on December 11, 2021. Retrieved July 18, 2021.
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Shutler, Ali (October 9, 2022). "Taylor Swift organises her lyrics into three 'dorky' pen-themed categories". NME. Retrieved October 18, 2022.
Browne, Erin (October 21, 2022). "All of Taylor Swift's Famously Devastating Track 5's, Ranked". Vulture. Retrieved October 27, 2022.
"NMPA to Honor Taylor Swift with Songwriter Icon Award Among Other 2021 Annual Meeting Honorees". National Music Publishers' Association. May 24, 2021. Retrieved May 24, 2021.
Linker, Damon (November 26, 2021). "Taylor Swift, Phoebe Bridgers, and Rihanna: How women took over songwriting". The Week. Retrieved November 28, 2021.
Greco, Patti (November 13, 2017). "A Harvard Professor Critiques Taylor Swift's New Poems". Cosmopolitan. Retrieved December 21, 2021.
Sheffield, Rob (October 13, 2023). "Taylor Swift's 'Eras Tour' Movie Will Make You Sing, Scream, and Sob". Rolling Stone. Retrieved December 8, 2023.
Zacharek, Stephanie (December 14, 2023). "The Eras Tour Movie Is Irresistible No Matter How Much You Think You Like Taylor Swift". TIME. Retrieved December 8, 2023.
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Aramesh, Waiss David (March 18, 2023). "Taylor Swift's The Eras Tour Is a 3-Hour Career-Spanning Victory Lap". Rolling Stone. OCLC 1787396. Archived from the original on March 18, 2023. Retrieved June 30, 2023.
Gambles, Sarah (July 23, 2023). "The ubiquitous power of Taylor Swift". Deseret News. Retrieved July 23, 2023.
McCormick, Neil (March 18, 2023). "Taylor Swift: The Eras Tour, review: a roaring spectacle of a comeback". The Daily Telegraph. Archived from the original on March 18, 2023. Retrieved March 18, 2023.
Kornhaber, Spencer (March 18, 2023). "What Made Taylor Swift's Concert Unbelievable". The Atlantic. Retrieved June 30, 2023.
Foggatt, Tyler (June 3, 2023). "Look What Taylor Made Us Do". The New Yorker. Retrieved June 30, 2023.
Seibert, Brian (August 9, 2023). "How to Command a Stage Without Great Dance Moves (Taylor's Version)". The New York Times. Retrieved August 11, 2023.
Krelenstein, Greg (May 21, 2018). "TAYLOR SWIFT'S REPUTATION TOUR IS A POP TRIUMPH". V. Archived from the original on May 22, 2018. Retrieved May 22, 2018.
Frere-Jones, Sasha (November 3, 2008). "Prodigy". The New Yorker. Retrieved June 30, 2023.
Horton, Adrian (March 18, 2023). "Taylor Swift review – pop's hardest-working star gives Eras tour her all". The Guardian. Archived from the original on March 18, 2023. Retrieved March 18, 2023.
Kaplan, Ilana (March 18, 2023). "Taylor Swift's 'Eras' tour is a thrilling spectacle from a pop mastermind". i. Archived from the original on March 18, 2023. Retrieved March 18, 2023.
Young, Alex (March 27, 2023). "Taylor Swift's "The Eras Tour" Is a Triumph of Spectacle and Stamina: Review". Consequence. Retrieved June 30, 2023.
Lipshutz, Jason (March 18, 2023). "The 13 Best Moments From Taylor Swift's Eras Tour Kickoff". Billboard. Retrieved July 1, 2023.
O'Connor, Roisin (June 8, 2018). "Taylor Swift 'reputation' stadium tour review: Dazzling pop spectacle from the star who doesn't stand still". The Independent. Archived from the original on June 30, 2023. Retrieved December 22, 2019.Savage, Mark (March 18, 2023). "Taylor Swift launches Eras tour with three-hour, 44-song set". BBC News. Archived from the original on March 18, 2023. Retrieved March 18, 2023. Sisario, Ben (November 5, 2023). "How Taylor Swift's Eras Tour Conquered the World". The New York Times. Retrieved August 12, 2023. DeVille, Chris (July 12, 2018). "Big Reputation: A Trip To Taylor Swift's Hyper-Maximalist Stadium Tour". Stereogum. Retrieved June 30, 2023.
Procell, Carlie; Padilla, Ramon (April 28, 2023). "Taylor Swift tour has many 'eras.' We tracked her movements to give you the look and feel". USA Today. Retrieved June 30, 2023.
"Taylor Swift Shares Stunning 'Wildest Dreams' Performance from Grammy Museum". Billboard. January 5, 2016. Retrieved October 29, 2023.
Burgham, Lydia (November 10, 2018). "Taylor Swift in Auckland, reviewed: Despite the snakes, her Reputation shines on". The Spinoff. Retrieved December 10, 2019.
Dodd, Sophie (November 15, 2023). "All About Taylor Swift's Parents, Scott and Andrea Swift". People. Retrieved December 3, 2023.
Swift, Taylor (March 15, 2013). ""Sparks Fly" (acoustic) Live on the RED Tour!" – via YouTube.
Lewis, Randy (April 3, 2011). "Academy of Country Music Awards: Las Vegas welcomes Miranda Lambert, Taylor Swift with open arms". Los Angeles Times. Retrieved August 20, 2023.
Ritchie, Mike (March 8, 2020). "Why Taylor Swift is making the ukulele cool again". The Herald. Retrieved July 1, 2023.
Gensler, Andy (August 17, 2023). "The Showgoer: The Greatest Show On Earth — Taylor Swift's 'Eras Tour' — Is All That And Far More". Pollstar. Retrieved August 19, 2023.
Sheffield, Rob (May 9, 2018). "Why Taylor Swift's 'Reputation' Tour Is Her Finest Yet". Rolling Stone. Retrieved June 30, 2023.
Willman, Chris (May 16, 2018). "Taylor Swift's 'Reputation' Tour Has Bad Blood, Good Will, Sex Appeal and Serpents". Variety. Retrieved December 22, 2019.
Willman, Chris (March 18, 2023). "Taylor Swift's 'Eras' Show Is a Three-Hour, 44-Song Epic That Leaves 'Em Wanting More: Concert Review". Variety. Archived from the original on March 18, 2023. Retrieved June 30, 2018.
Ordoña, Michael (September 9, 2022). "Taylor Swift wants an Oscar. So she took 'All Too Well' to TIFF". Los Angeles Times. Retrieved September 10, 2022.
CMT.com Staff (May 4, 2011). "Taylor Swift's "Mean" Video Debuts Friday". CMT. Archived from the original on June 19, 2019. Retrieved June 19, 2019.
Anitai, Tamar (August 27, 2010). "Video Premiere: Taylor Swift, 'Mine'". MTV News. Archived from the original on April 29, 2019. Retrieved June 19, 2019.
Bonaguro, Alison (May 6, 2011). "OFFSTAGE: Taylor Swift Isn't 'Mean' at All, Director Says". CMT News. Archived from the original on June 19, 2019. Retrieved June 20, 2019.
Tailor, Leena (September 1, 2017). "Exclusive: Taylor Swift's Director Joseph Kahn on How Her Image Invokes a Double Standard: 'She's a Genius'". Entertainment Tonight. Archived from the original on June 19, 2019.
O'Connell, Michael (October 9, 2015). "Taylor Swift and Jimmy Fallon Among Early Emmy Winners". The Hollywood Reporter. Archived from the original on June 19, 2019.
Forbes, Jihan (May 14, 2015). "Peep Taylor Swift's Star-Studded Cast for Her 'Bad Blood' Music Video". The Fashion Spot. Retrieved May 13, 2020.
"9 Things You Might Have Missed in Taylor Swift's Netflix Concert Film". E! News. December 31, 2018. Retrieved September 10, 2022.
Spanos, Brittany (April 25, 2019). "Watch Taylor Swift, Brendon Urie's Colorful 'ME!' Video". Rolling Stone. Archived from the original on April 26, 2019. Retrieved April 25, 2019.
Moore, Sam (August 23, 2019). "Watch Taylor Swift's colourful new video for 'Lover'". NME. Archived from the original on August 27, 2019. Retrieved August 27, 2019.
Zemler, Emily (June 17, 2019). "Watch Taylor Swift Reunite With Katy Perry in 'You Need to Calm Down' Video". Rolling Stone. Archived from the original on June 17, 2019. Retrieved June 17, 2019.
Mylrea, Hannah (February 28, 2020). "Every incredible Easter Egg in Taylor Swift's 'The Man' video". NME. Retrieved March 9, 2020.
Spanos, Brittany; Legaspi, Althea (July 24, 2020). "Taylor Swift Blends Fantastical With Personal in 'Cardigan' Video". Rolling Stone. Retrieved July 27, 2020.
"Justin Bieber & Megan Thee Stallion Lead 2021 MTV VMA Nominations". Billboard. Retrieved August 17, 2021.
Weatherby, Taylor (February 5, 2023). "Taylor Swift Makes GRAMMY History (Again) With Best Music Video Win For "All Too Well: The Short Film"". Grammy Awards. Retrieved February 6, 2023.
Lansky, Sam (December 6, 2023). "Taylor Swift Is TIME's 2023 Person of the Year". Time. Retrieved December 6, 2023.
"Taylor Swift". The Recording Academy. Archived from the original on August 12, 2016. Retrieved August 3, 2016.
Friedlander, Whitney (September 10, 2015). "Taylor Swift, Jimmy Fallon Among Juried Emmy Award Winners". Variety. Archived from the original on September 15, 2015. Retrieved August 3, 2016.
"Taylor Swift dominates AMAs with 6 wins, extending lead as show's most-decorated artist". KTRK-TV. November 21, 2022. Retrieved November 21, 2022.
Grein, Paul (November 19, 2023). "After the 2023 Billboard Music Awards, Who Is the All-Time Biggest Winner?". Billboard. Retrieved November 19, 2023.
See Guinness World Records by Taylor Swift
Lewis, Randy (November 4, 2013). "Taylor Swift to receive rare Pinnacle Award at CMA Awards Nov. 6". Los Angeles Times. Retrieved May 13, 2020.
"Taylor Swift Nashville Tickets". Excite. Archived from the original on February 3, 2015. Retrieved February 2, 2015.
Shelburne, Craig (October 18, 2010). "Taylor Swift Named NSAI's Songwriter-Artist of the Year". CMT. Archived from the original on March 14, 2014. Retrieved February 2, 2015.
"Songwriters Hall of Fame". Songwriters Hall of Fame. Archived from the original on November 29, 2014. Retrieved February 2, 2015.
"The 100 Greatest Songwriters of All Time". Rolling Stone. Archived from the original on September 2, 2017. Retrieved August 28, 2017.
Polanco, Luis (April 5, 2016). "Taylor Swift to Receive First-Ever Taylor Swift Award From BMI". Billboard. Retrieved October 21, 2020.
Jolly, Nathan (November 17, 2019). "Why Taylor Swift is to blame for latest twist in music rights drama". News.com.au. Retrieved November 17, 2019.
"10 Life mantras by Taylor Swift to live by". India Today. December 13, 2016. Archived from the original on February 9, 2019. Retrieved July 16, 2020.
Lipshutz, Jason (December 11, 2019). "Billboard Woman of the Decade Taylor Swift: 'I Do Want My Music to Live On'". Billboard. Retrieved December 11, 2019.
"Taylor Swift to receive BRITs Global Icon award". Official Charts Company. May 9, 2021. Retrieved May 10, 2021.
"Taylor Swift to receive Global Icon Award!". Brit Awards. May 9, 2021. Retrieved May 10, 2021.
Paine, Andre (February 22, 2023). "Taylor Swift wins IFPI's 2022 Global Recording Artist Of The Year Award". Music Week. Retrieved February 22, 2023.
Brandle, Lars (November 5, 2023). "Taylor Swift's '1989 (Taylor's Version)' Debuts at U.K. No. 1 With 'Massive' Sales". Billboard. Retrieved November 5, 2023.
"Female artists with the most Irish Number 1 albums since 2000". Official Charts Company. November 5, 2020. Retrieved February 23, 2021.
Wang, Dennis (April 16, 2021). "Taylor Swift's Fearless hits the right note in China, again". People's Daily. Retrieved June 26, 2021.
Brandle, Lars (July 7, 2023). "Taylor Swift Sets Chart Record In Australia With Top-Five Sweep". Billboard. Retrieved February 13, 2024.
Brandle, Lars (February 9, 2024). "Ahead of 'The Eras Tour' of Australia, Taylor Swift Sweeps Top 5". Billboard. Retrieved February 13, 2024.
"Taylor beats Swift". Australian Recording Industry Association. July 14, 2023. Archived from the original on July 14, 2023. Retrieved July 19, 2023.
"Taylor sweeps the record". Australian Recording Industry Association. July 7, 2023. Retrieved July 7, 2023.
Cumulative touring gross:
"Top Touring Artist of the Pollstar Era" (PDF). Pollstar. June 10, 2022. Archived (PDF) from the original on August 5, 2022. Retrieved August 4, 2022.
Allen, Bob (September 26, 2023). "What A Friggin' Year! 2023 Boxoffice Results Remain At Record Highs". Pollstar. Retrieved October 18, 2023.
Gensler, Andy (December 8, 2023). "Taylor Swift Sets All-Time Touring Record With $1 Billion Gross". Pollstar. Archived from the original on December 8, 2023. Retrieved December 8, 2023.
Willman, Chris (December 21, 2020). "Taylor Swift's 'Evermore' Sells a Million Worldwide in First Week". Variety. Archived from the original on January 11, 2021. Retrieved December 21, 2020.
Paine, Andre (December 22, 2022). "Taylor Swift Achieves More Than 6 Million Global Units for Midnights and 37 Billion Total Streams in 2022". Music Week. Archived from the original on December 22, 2022. Retrieved July 19, 2023.
Young, Alex (October 31, 2022). "Taylor Swift broke 73 records with release of new album Midnights". Consequence. Archived from the original on October 31, 2022. Retrieved July 19, 2023.
Grein, Paul (November 8, 2023). "Taylor Swift Is Apple Music's 2023 Artist of the Year". Billboard. Retrieved November 8, 2023.
Willman, Chris (October 28, 2023). "Taylor Swift Beats Her Own Spotify Record for Most Single-Day Streams for an Artist With '1989 (Taylor's Version)' Release". Variety. Archived from the original on October 29, 2023. Retrieved October 29, 2023.
@billboardcharts (January 19, 2022). "Most entries on the #Global200 chart in a single week" (Tweet) – via Twitter.
"Taylor Swift Chart History (Billboard Global 200)". Billboard. Retrieved July 17, 2023.
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Zellner, Xander (January 25, 2024). "Taylor Swift Tallies Record-Extending 95th Week at No. 1 on Artist 100 Chart". Billboard. Retrieved January 26, 2024.
Caulfield, Keith (December 31, 2023). "Taylor Swift Surpasses Elvis Presley for Most Weeks at No. 1 on Billboard 200 Among Soloists". Billboard. Retrieved January 3, 2024.
Trust, Gary (January 22, 2024). "Ariana Grande's 'Yes, And?' Debuts at No. 1 on Billboard Hot 100". Billboard. Retrieved January 22, 2024.
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Trust, Gary (July 28, 2023). "Taylor Swift Breaks Record for Most No. 1s on Pop Airplay Chart As 'Cruel Summer' Becomes Her 12th". Billboard. Archived from the original on September 29, 2023. Retrieved October 19, 2023.
Caulfield, Keith (December 3, 2023). "Taylor Swift Makes History With Five of the Top 10 Albums on the Billboard 200". Billboard. Retrieved January 3, 2024.
Caulfield, Keith (July 17, 2023). "Taylor Swift Has 11 Albums on the Billboard 200 Chart for the First Time". Billboard. Retrieved July 19, 2023.
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Caulfield, Keith (December 29, 2023). "Taylor Swift Has the Top Four on the Album Sales Chart for the First Time". Billboard. Retrieved January 3,
gitextract_st7_oioa/ ├── .gitignore ├── LICENSE ├── README.md ├── exercise.md ├── lecture.md ├── minbpe/ │ ├── __init__.py │ ├── base.py │ ├── basic.py │ ├── gpt4.py │ └── regex.py ├── requirements.txt ├── tests/ │ ├── __init__.py │ ├── taylorswift.txt │ └── test_tokenizer.py └── train.py
SYMBOL INDEX (41 symbols across 5 files)
FILE: minbpe/base.py
function get_stats (line 13) | def get_stats(ids, counts=None):
function merge (line 25) | def merge(ids, pair, idx):
function replace_control_characters (line 44) | def replace_control_characters(s: str) -> str:
function render_token (line 57) | def render_token(t: bytes) -> str:
class Tokenizer (line 66) | class Tokenizer:
method __init__ (line 69) | def __init__(self):
method train (line 76) | def train(self, text, vocab_size, verbose=False):
method encode (line 80) | def encode(self, text):
method decode (line 84) | def decode(self, ids):
method _build_vocab (line 88) | def _build_vocab(self):
method save (line 97) | def save(self, file_prefix):
method load (line 140) | def load(self, model_file):
FILE: minbpe/basic.py
class BasicTokenizer (line 15) | class BasicTokenizer(Tokenizer):
method __init__ (line 17) | def __init__(self):
method train (line 20) | def train(self, text, vocab_size, verbose=False):
method decode (line 51) | def decode(self, ids):
method encode (line 57) | def encode(self, text):
FILE: minbpe/gpt4.py
function bpe (line 11) | def bpe(mergeable_ranks, token, max_rank):
function recover_merges (line 29) | def recover_merges(mergeable_ranks):
class GPT4Tokenizer (line 57) | class GPT4Tokenizer(RegexTokenizer):
method __init__ (line 60) | def __init__(self):
method _encode_chunk (line 81) | def _encode_chunk(self, text_bytes):
method decode (line 87) | def decode(self, ids):
method train (line 95) | def train(self, text, vocab_size, verbose=False):
method save (line 103) | def save(self, file_prefix):
method load (line 106) | def load(self, model_file):
method save_vocab (line 109) | def save_vocab(self, vocab_file):
FILE: minbpe/regex.py
class RegexTokenizer (line 22) | class RegexTokenizer(Tokenizer):
method __init__ (line 24) | def __init__(self, pattern=None):
method train (line 36) | def train(self, text, vocab_size, verbose=False):
method register_special_tokens (line 72) | def register_special_tokens(self, special_tokens):
method decode (line 78) | def decode(self, ids):
method _encode_chunk (line 92) | def _encode_chunk(self, text_bytes):
method encode_ordinary (line 111) | def encode_ordinary(self, text):
method encode (line 123) | def encode(self, text, allowed_special="none_raise"):
FILE: tests/test_tokenizer.py
function unpack (line 17) | def unpack(text):
function test_encode_decode_identity (line 54) | def test_encode_decode_identity(tokenizer_factory, text):
function test_gpt4_tiktoken_equality (line 63) | def test_gpt4_tiktoken_equality(text):
function test_gpt4_tiktoken_equality_special_tokens (line 72) | def test_gpt4_tiktoken_equality_special_tokens():
function test_wikipedia_example (line 81) | def test_wikipedia_example(tokenizer_factory):
function test_save_load (line 110) | def test_save_load(special_tokens):
Condensed preview — 15 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (243K chars).
[
{
"path": ".gitignore",
"chars": 65,
"preview": "__pycache__/\n.DS_Store\nmodels/**/*\n*.pytest_cache\n*.model\n*.vocab"
},
{
"path": "LICENSE",
"chars": 1063,
"preview": "MIT License\n\nCopyright (c) 2024 Andrej\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof "
},
{
"path": "README.md",
"chars": 9270,
"preview": "# minbpe\n\nMinimal, clean code for the (byte-level) Byte Pair Encoding (BPE) algorithm commonly used in LLM tokenization."
},
{
"path": "exercise.md",
"chars": 3592,
"preview": "# exercise\n\nBuild your own GPT-4 Tokenizer!\n\n### Step 1\n\nWrite the `BasicTokenizer` class, with the following three core"
},
{
"path": "lecture.md",
"chars": 8507,
"preview": "# LLM Tokenization\n\nHi everyone, today we are going to look at Tokenization in Large Language Models (LLMs). Sadly, toke"
},
{
"path": "minbpe/__init__.py",
"chars": 128,
"preview": "from .base import Tokenizer\nfrom .basic import BasicTokenizer\nfrom .regex import RegexTokenizer\nfrom .gpt4 import GPT4To"
},
{
"path": "minbpe/base.py",
"chars": 6879,
"preview": "\"\"\"\nContains the base Tokenizer class and a few common helper functions.\nThe base class also contains the (common) save/"
},
{
"path": "minbpe/basic.py",
"chars": 2883,
"preview": "\"\"\"\nMinimal (byte-level) Byte Pair Encoding tokenizer.\n\nAlgorithmically follows along the GPT tokenizer:\nhttps://github."
},
{
"path": "minbpe/gpt4.py",
"chars": 5810,
"preview": "\"\"\"\nImplements the GPT-4 Tokenizer as a light wrapper around the RegexTokenizer.\nNote that this is a pretrained tokenize"
},
{
"path": "minbpe/regex.py",
"chars": 7344,
"preview": "\"\"\"\nMinimal (byte-level) Byte Pair Encoding tokenizer.\n\nAlgorithmically follows along the GPT tokenizer:\nhttps://github."
},
{
"path": "requirements.txt",
"chars": 14,
"preview": "regex\ntiktoken"
},
{
"path": "tests/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "tests/taylorswift.txt",
"chars": 185561,
"preview": "Copy paste of the Wikipedia article on Taylor Swift, as of Feb 16, 2024.\n---\n\nMain menu\n\nWikipediaThe Free Encyclopedia\n"
},
{
"path": "tests/test_tokenizer.py",
"chars": 6185,
"preview": "import pytest\nimport tiktoken\nimport os\n\nfrom minbpe import BasicTokenizer, RegexTokenizer, GPT4Tokenizer\n\n# -----------"
},
{
"path": "train.py",
"chars": 882,
"preview": "\"\"\"\nTrain our Tokenizers on some data, just to see them in action.\nThe whole thing runs in ~25 seconds on my laptop.\n\"\"\""
}
]
About this extraction
This page contains the full source code of the karpathy/minbpe GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 15 files (232.6 KB), approximately 62.2k tokens, and a symbol index with 41 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.