| |
| from typing import Any, Dict, Optional |
|
|
| from swift.llm import DatasetMeta, ResponsePreprocessor, load_dataset, register_dataset |
|
|
|
|
| class CustomPreprocessor(ResponsePreprocessor): |
| prompt = """Task: Based on the given two sentences, provide a similarity score between 0.0 and 5.0. |
| Sentence 1: {text1} |
| Sentence 2: {text2} |
| Similarity score: """ |
|
|
| def preprocess(self, row: Dict[str, Any]) -> Optional[Dict[str, Any]]: |
| return super().preprocess({ |
| 'query': self.prompt.format(text1=row['text1'], text2=row['text2']), |
| 'response': f"{row['label']:.1f}" |
| }) |
|
|
|
|
| register_dataset( |
| DatasetMeta( |
| ms_dataset_id='swift/stsb', |
| hf_dataset_id='SetFit/stsb', |
| preprocess_func=CustomPreprocessor(), |
| )) |
|
|
| if __name__ == '__main__': |
| dataset = load_dataset(['swift/stsb'])[0] |
| print(f'dataset: {dataset}') |
| print(f'dataset[0]: {dataset[0]}') |
|
|
