SYMBOL INDEX (38 symbols across 6 files)

FILE: example_chat_completion.py
  function main (line 11) | def main(

FILE: example_text_completion.py
  function main (line 9) | def main(

FILE: llama/generation.py
  class Message (line 25) | class Message(TypedDict):
  class CompletionPrediction (line 30) | class CompletionPrediction(TypedDict, total=False):
  class ChatPrediction (line 36) | class ChatPrediction(TypedDict, total=False):
  class Llama (line 51) | class Llama:
    method build (line 53) | def build(
    method __init__ (line 125) | def __init__(self, model: Transformer, tokenizer: Tokenizer):
    method generate (line 130) | def generate(
    method text_completion (line 233) | def text_completion(
    method chat_completion (line 284) | def chat_completion(
  function sample_top_p (line 398) | def sample_top_p(probs, p):

FILE: llama/model.py
  class ModelArgs (line 20) | class ModelArgs:
  class RMSNorm (line 34) | class RMSNorm(torch.nn.Module):
    method __init__ (line 35) | def __init__(self, dim: int, eps: float = 1e-6):
    method _norm (line 52) | def _norm(self, x):
    method forward (line 65) | def forward(self, x):
  function precompute_freqs_cis (line 80) | def precompute_freqs_cis(dim: int, end: int, theta: float = 10000.0):
  function reshape_for_broadcast (line 107) | def reshape_for_broadcast(freqs_cis: torch.Tensor, x: torch.Tensor):
  function apply_rotary_emb (line 132) | def apply_rotary_emb(
  function repeat_kv (line 164) | def repeat_kv(x: torch.Tensor, n_rep: int) -> torch.Tensor:
  class Attention (line 176) | class Attention(nn.Module):
    method __init__ (line 178) | def __init__(self, args: ModelArgs):
    method forward (line 253) | def forward(
  class FeedForward (line 307) | class FeedForward(nn.Module):
    method __init__ (line 308) | def __init__(
    method forward (line 347) | def forward(self, x):
  class TransformerBlock (line 351) | class TransformerBlock(nn.Module):
    method __init__ (line 352) | def __init__(self, layer_id: int, args: ModelArgs):
    method forward (line 386) | def forward(
  class Transformer (line 413) | class Transformer(nn.Module):
    method __init__ (line 414) | def __init__(self, params: ModelArgs):
    method forward (line 457) | def forward(self, tokens: torch.Tensor, start_pos: int):

FILE: llama/tokenizer.py
  class Tokenizer (line 14) | class Tokenizer:
    method __init__ (line 16) | def __init__(self, model_path: str):
    method encode (line 38) | def encode(self, s: str, bos: bool, eos: bool) -> List[int]:
    method decode (line 58) | def decode(self, t: List[int]) -> str:

FILE: setup.py
  function get_requirements (line 7) | def get_requirements(path: str):