SYMBOL INDEX (27 symbols across 7 files)

FILE: SII_MDP/regression_evaluate.py
  function test_regression (line 7) | def test_regression():
  function draw_regression (line 118) | def draw_regression():

FILE: SII_MDP/regression_test.py
  function generate_prompt (line 11) | def generate_prompt(prompt_instruction, prompt_input):
  function generate_prediction (line 15) | def generate_prediction(model_path,data_path):

FILE: SII_MDP/sii_test.py
  function generate_prompt (line 11) | def generate_prompt(prompt_instruction, prompt_input):
  function generate_prediction (line 15) | def generate_prediction(model_path,data_path):

FILE: evaluate_matbench.py
  function generate_prompt (line 15) | def generate_prompt(instruction, input=None):
  function get_first_number (line 29) | def get_first_number(string):

FILE: inference.py
  function generate_prompt (line 6) | def generate_prompt(instruction, input=None):
  function process_response (line 20) | def process_response(response):
  function evaluate (line 24) | def evaluate(instruction,

FILE: train.py
  class ModelArguments (line 46) | class ModelArguments:
  class DataArguments (line 51) | class DataArguments:
  class TrainingArguments (line 56) | class TrainingArguments(transformers.TrainingArguments):
  function smart_tokenizer_and_embedding_resize (line 66) | def smart_tokenizer_and_embedding_resize(
  function _tokenize_fn (line 89) | def _tokenize_fn(strings: Sequence[str], tokenizer: transformers.PreTrai...
  function preprocess (line 113) | def preprocess(
  class SupervisedDataset (line 128) | class SupervisedDataset(Dataset):
    method __init__ (line 131) | def __init__(self, data_path: str, tokenizer: transformers.PreTrainedT...
    method __len__ (line 150) | def __len__(self):
    method __getitem__ (line 153) | def __getitem__(self, i) -> Dict[str, torch.Tensor]:
  class DataCollatorForSupervisedDataset (line 158) | class DataCollatorForSupervisedDataset(object):
    method __call__ (line 163) | def __call__(self, instances: Sequence[Dict]) -> Dict[str, torch.Tensor]:
  function make_supervised_data_module (line 176) | def make_supervised_data_module(tokenizer: transformers.PreTrainedTokeni...
  function train (line 183) | def train():

FILE: utils.py
  function _make_r_io_base (line 12) | def _make_r_io_base(f, mode: str):
  function jload (line 18) | def jload(f, mode="r"):