| from typing import Dict |
|
|
| def add_eos(example, eos_token): |
| """在 labels 部分末尾添加 eos token |
| """ |
| if "text" in example and not example["text"].endswith(eos_token): |
| example["text"] = example["text"] + eos_token |
| elif "completion" in example and not example["completion"].endswith(eos_token): |
| example["completion"] = example["completion"] + eos_token |
| return example |
|
|
| def tokenize(example, processing_class) -> Dict: |
|
|
| output = dict(example) |
| prompt_ids = processing_class( |
| text=example["prompt"], add_special_tokens=False |
| )["input_ids"] |
| completion_ids = processing_class( |
| text=example["completion"], add_special_tokens=False |
| )["input_ids"] |
| input_ids = prompt_ids + completion_ids |
| |
| |
| completion_mask = [0] * len(prompt_ids) + [1] * len(completion_ids) |
| output["input_ids"] = input_ids |
| output["completion_mask"] = completion_mask |
|
|
| return output |
|
|
| def tokenize_instruction_example(example: Dict, processing_class) -> Dict: |
| eos_token = processing_class.eos_token |
| eos_example = add_eos(example, eos_token) |
| tokenized_example = tokenize(eos_example, processing_class) |
| |
| return tokenized_example |
|
|
|
|
| def tokenize_conversation_example(example: Dict, processing_class) -> Dict: |
| ... |
