---
license: apache-2.0
task_categories:
- question-answering
- text-generation
language:
- en
size_categories:
- 10K<n<100K
---

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6489e1e3eb763749c663f40c/ZKzKrpYNjiFHLZtH062GW.jpeg)



Reference : "A Question-Entailment Approach to Question Answering". Asma Ben Abacha and Dina Demner-Fushman. BMC Bioinformatics, 2019."
<br/>This is an update of Keivalya Pandya's dataset (keivalya/MedQuad-MedicalQnADataset).

<h1> Content </h1>
There are medical questions and corresponding responses in a prompt format for chat or instruct model types
<br/>In order to fine tuned LLM with small HW (1 or 2 GPU with 14 Go)
<br/>Rows above 128 tokens have been deleted.
<br/>Rows have been truncated to a line break or a sentence end in order to keep a correct meaning

<h2> Script to download the dataset </h2>
<br/>from datasets import load_dataset
<br/>dataset_name = "Laurent1/MedQuad-MedicalQnADataset_128tokens_max"
<br/>dataset = load_dataset(dataset_name, split="train")