nuvocare/MSD_instruct

---
dataset_info:
features:
- name: User
dtype: string
- name: Category
dtype: string
- name: Language
dtype:
class_label:
names:
'0': english
'1': french
'2': german
'3': spanish
- name: Topic1
dtype: string
- name: Topic2
dtype: string
- name: Topic3
dtype: string
- name: Text
dtype: string
- name: Question
dtype: string
splits:
- name: train
num_bytes: 133987453
num_examples: 79898
- name: test
num_bytes: 44598046
num_examples: 26639
download_size: 107452363
dataset_size: 178585499
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
license: apache-2.0
task_categories:
- text-generation
- text2text-generation
language:
- de
- es
- fr
- en
tags:
- medical
size_categories:
- 10K<n<100K
---

# MSD_manual_topics_user_base

This dataset has been built with the website https://www.msdmanuals.com/ provided by Merck & Co for the greater audience.

The MSD manual is an essential source of knowledge for many topics related to symptoms, diseases, health and other related topics. The manual makes an extra effort to make it available both for professionals and patients by having two distinct version.
The content, while being labelled the same, differs by the type of user in order to facilitate understanding for patients or give clear details for professional. The manual is available in different languages.

This dataset focuses on spanish, german, english and french content about health topics and symptoms. The content is tagged by 2 to 3 medical topics and flagged by user's type and languages.

It consists of roughly 21M words representing 45M tokens.

This dataset is built for instruction fine-tuning. We built the "Question" by querying a vanilla Mistral 7B model with the following prompt:

```python
You will be asked to create one or several questions in the appropriate language based on three elements. Return the ouptuts in the format of the examples. If asked several, splits the answers with a "&" sign.
Example input:
For question 1 : elements are musculoskeletal and connective tissue disorders, Autoimmune Myositis and Diagnosis of Autoimmune Myositis and language is english
Example output:
["Question 1", "musculoskeletal and connective tissue disorders, Autoimmune Myositis and Diagnosis of Autoimmune Myositis", "English", "How to diagnose a autoimmune Myositis ? "]

Example input:
For question 514 : elements are troubles cardiaques et vasculaires, Bloc auriculoventriculaire and Introduction and language is french
Example output:
["Question 514", "troubles cardiaques et vasculaires, Bloc auriculoventriculaire and Introduction", "French", "Donne moi des informations introductives sur le bloc auriculoventriculaire."]

Example input:
For question 514 : elements are troubles cardiaques et vasculaires, Bloc auriculoventriculaire and Introduction and language is french For question 1 : elements are musculoskeletal and connective tissue disorders, Autoimmune Myositis and Diagnosis of Autoimmune Myositis and language is english
Example output:
["Question 514", "troubles cardiaques et vasculaires, Bloc auriculoventriculaire and Introduction", "French", "Donne moi des informations introductives sur le bloc auriculoventriculaire."] & ["Question 1", "musculoskeletal and connective tissue disorders, Autoimmune Myositis and Diagnosis of Autoimmune Myositis", "English", "How to diagnose a autoimmune Myositis ? "]
[/INST]
```

This dataset can be used to fine-tune a model to a task of supproting patients and clinicians to be better informed in an adapted manner.

An instruct-free version is available here : https://huggingface.co/datasets/nuvocare/MSD_manual_topics_user_base

This dataset is built using the website : https://www.msdmanuals.com/ provided by Merck & Co.
All credits of the contents are for the MSD organization.

[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

原始信息汇总

数据集概述

数据集信息

特征

• User: 字符串类型
• Category: 字符串类型
• Language: 分类标签类型，包含以下类别：
  • 0: 英语
  • 1: 法语
  • 2: 德语
  • 3: 西班牙语
• Topic1: 字符串类型
• Topic2: 字符串类型
• Topic3: 字符串类型
• Text: 字符串类型
• Question: 字符串类型

数据分割

• train:
  • 字节数: 133987453
  • 样本数: 79898
• test:
  • 字节数: 44598046
  • 样本数: 26639

数据集大小

• 下载大小: 107452363 字节
• 数据集大小: 178585499 字节

配置

• default:
  • 训练数据文件路径: data/train-*
  • 测试数据文件路径: data/test-*

许可证

• apache-2.0

任务类别

• 文本生成
• 文本到文本生成

语言

• 德语
• 西班牙语
• 法语
• 英语

标签

• 医疗

数据集大小类别

• 10K<n<100K