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Browse files- README.md +49 -0
- my_dataset.py +16 -9
README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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task_categories:
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- text-generation
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language:
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- zh
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tags:
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- medical
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size_categories:
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- 100K<n<1M
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---
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# Dataset Card for Huatuo_knowledge_graph_qa
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## Dataset Description
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- **Homepage: https://www.huatuogpt.cn/**
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- **Repository: https://github.com/FreedomIntelligence/Huatuo-26M**
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- **Paper: https://arxiv.org/abs/2305.01526**
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- **Leaderboard:**
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- **Point of Contact:**
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### Dataset Summary
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We are pleased to announce the release of our evaluation dataset, a subset of the Huatuo-26M. This dataset contains 6,000 entries that we used for Natural Language Generation (NLG) experimentation in our associated research paper.
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We encourage researchers and developers to use this evaluation dataset to gauge the performance of their own models. This is not only a chance to assess the accuracy and relevancy of generated responses but also an opportunity to investigate their model's proficiency in understanding and generating complex medical language.
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Note: All the data points have been anonymized to protect patient privacy, and they adhere strictly to data protection and privacy regulations.
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## Citation
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```
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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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my_dataset.py
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from datasets import DatasetInfo, Features, Split, SplitGenerator, GeneratorBasedBuilder, Value
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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":
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"answers":
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}),
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supervised_keys=("questions", "answers"),
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homepage="https://github.com/FreedomIntelligence/
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citation=
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)
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def _split_generators(self, dl_manager):
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-
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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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from datasets import DatasetInfo, Features, Split, SplitGenerator, GeneratorBasedBuilder, Value
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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": Value("string"),
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"answers": 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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test_path = "test_datasets.jsonl"
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return [
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SplitGenerator(name=Split.TEST, gen_kwargs={"filepath": test_path}),
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]
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