| # Copyright (c) Alibaba, Inc. and its affiliates. | |
| 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]}') | |