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| from datasets import DatasetInfo, Features, Split, SplitGenerator, GeneratorBasedBuilder, Value, Sequence |
| import json |
|
|
| class MyDataset(GeneratorBasedBuilder): |
| def _info(self): |
| return DatasetInfo( |
| features=Features({ |
| "questions": Sequence(Value("string")), |
| "answers": Sequence(Value("string")) |
| }), |
| supervised_keys=("questions", "answers"), |
| homepage="https://github.com/FreedomIntelligence/Huatuo-26M", |
| citation=''' |
| @misc{li2023huatuo26m, |
| title={Huatuo-26M, a Large-scale Chinese Medical QA Dataset}, |
| author={Jianquan Li and Xidong Wang and Xiangbo Wu and Zhiyi Zhang and Xiaolong Xu and Jie Fu and Prayag Tiwari and Xiang Wan and Benyou Wang}, |
| year={2023}, |
| eprint={2305.01526}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CL} |
| } |
| |
| ''', |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| train_path = "train_datasets.jsonl" |
| validation_path = "validation_datasets.jsonl" |
| test_path = "test_datasets.jsonl" |
|
|
| return [ |
| SplitGenerator(name=Split.TRAIN, gen_kwargs={"filepath": train_path}), |
| SplitGenerator(name=Split.VALIDATION, gen_kwargs={"filepath": validation_path}), |
| SplitGenerator(name=Split.TEST, gen_kwargs={"filepath": test_path}), |
| ] |
|
|
| def _generate_examples(self, filepath): |
| with open(filepath, encoding="utf-8") as f: |
| for id_, row in enumerate(f): |
| |
| |
| data = json.loads(row) |
| yield id_, { |
| "questions": data["questions"], |
| "answers": data["answers"], |
| } |
|
|
| if __name__ == '__main__': |
| from datasets import load_dataset |
|
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| dataset = load_dataset("my_dataset.py") |
|
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| print() |