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license: apache-2.0 |
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task_categories: |
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- question-answering |
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- text-generation |
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language: |
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- en |
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size_categories: |
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- 10K<n<100K |
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--- |
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%3C!-- HTML_TAG_END --> |
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Reference : "A Question-Entailment Approach to Question Answering". Asma Ben Abacha and Dina Demner-Fushman. BMC Bioinformatics, 2019." |
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<br/>This is an update of Keivalya Pandya's dataset (keivalya/MedQuad-MedicalQnADataset). |
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<h1> Content </h1> |
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There are medical questions and corresponding responses in a prompt format for chat or instruct model types |
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<br/>In order to fine tuned LLM with small HW (1 or 2 GPU with 14 Go) |
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<br/>Rows above 128 tokens have been deleted. |
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<br/>Rows have been truncated to a line break or a sentence end in order to keep a correct meaning |
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<h2> Script to download the dataset </h2> |
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<br/>from datasets import load_dataset |
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<br/>dataset_name = "Laurent1/MedQuad-MedicalQnADataset_128tokens_max" |
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<br/>dataset = load_dataset(dataset_name, split="train") |
