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AnonNo2 commited on
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  1. README.md +49 -0
  2. my_dataset.py +16 -9
README.md CHANGED
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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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+
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+
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+
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+ ## Dataset Description
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+
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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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+
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+
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+
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+ ### Dataset Summary
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+
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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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+
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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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+
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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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+
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+
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+
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+
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+
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+
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+ ## Citation
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+
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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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+ ```
my_dataset.py CHANGED
@@ -1,29 +1,36 @@
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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/HuatuoGPT",
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- citation="...",
 
 
 
 
 
 
 
 
 
 
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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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+ 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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  )
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  def _split_generators(self, dl_manager):
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+
 
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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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