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