metadata
dataset_info:
features:
- name: messages
list:
- name: content
dtype: string
- name: role
dtype: string
splits:
- name: train
num_bytes: 902953
num_examples: 2446
download_size: 246445
dataset_size: 902953
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- text-generation
- text2text-generation
- question-answering
language:
- en
size_categories:
- 1K<n<10K
Description
The dataset is from medalpaca/medical_meadow_pubmed_causal, formatted as dialogues for speed and ease of use. Many thanks to author for releasing it.
Importantly, this format is easy to use via the default chat template of transformers, meaning you can use huggingface/alignment-handbook immediately, unsloth.
Structure
View online through viewer.
Note
We advise you to reconsider before use, thank you. If you find it useful, please like and follow this account.
Reference
The Ghost X was developed with the goal of researching and developing artificial intelligence useful to humans.
- HuggingFace: ghost-x
- Github: ghost-x-ai
- X / Twitter: ghostx_ai
- Website: ghost-x.org
Citation
@inproceedings{yu-etal-2019-detecting,
title = "Detecting Causal Language Use in Science Findings",
author = "Yu, Bei and
Li, Yingya and
Wang, Jun",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-1473",
doi = "10.18653/v1/D19-1473",
pages = "4664--4674",
}