|
--- |
|
dataset_info: |
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features: |
|
- name: prompt |
|
dtype: string |
|
- name: messages |
|
list: |
|
- name: role |
|
dtype: string |
|
- name: content |
|
dtype: string |
|
splits: |
|
- name: train_douban_sft |
|
num_bytes: 5567696 |
|
num_examples: 3086 |
|
- name: train_human_value_sft |
|
num_bytes: 806635 |
|
num_examples: 1007 |
|
- name: train_logi_qa_sft |
|
num_bytes: 666517 |
|
num_examples: 421 |
|
- name: train_ruozhiba_sft |
|
num_bytes: 228494 |
|
num_examples: 240 |
|
- name: train_segmentfault_sft |
|
num_bytes: 1068526 |
|
num_examples: 458 |
|
- name: train_wiki_sft |
|
num_bytes: 27611061 |
|
num_examples: 10603 |
|
- name: train_wikihow_sft |
|
num_bytes: 11069103 |
|
num_examples: 1485 |
|
- name: train_xhs_sft |
|
num_bytes: 2551884 |
|
num_examples: 1508 |
|
- name: train_zhihu_sft |
|
num_bytes: 13986060 |
|
num_examples: 5631 |
|
- name: train_sft |
|
num_bytes: 63555976 |
|
num_examples: 24439 |
|
- name: test_sft |
|
num_bytes: 228494 |
|
num_examples: 240 |
|
download_size: 67916523 |
|
dataset_size: 127340446 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: train_douban_sft |
|
path: data/train_douban_sft-* |
|
- split: train_human_value_sft |
|
path: data/train_human_value_sft-* |
|
- split: train_logi_qa_sft |
|
path: data/train_logi_qa_sft-* |
|
- split: train_ruozhiba_sft |
|
path: data/train_ruozhiba_sft-* |
|
- split: train_segmentfault_sft |
|
path: data/train_segmentfault_sft-* |
|
- split: train_wiki_sft |
|
path: data/train_wiki_sft-* |
|
- split: train_wikihow_sft |
|
path: data/train_wikihow_sft-* |
|
- split: train_xhs_sft |
|
path: data/train_xhs_sft-* |
|
- split: train_zhihu_sft |
|
path: data/train_zhihu_sft-* |
|
- split: train_sft |
|
path: data/train_sft-* |
|
- split: test_sft |
|
path: data/test_sft-* |
|
--- |
|
# COIG-CQIA-sft: COIG-CQIA for sft in alignment-handbook |
|
|
|
数据完全来自于[COIG-CQIA](https://huggingface.co/datasets/m-a-p/COIG-CQIA)。 |
|
|
|
暂时忽略了chinese_traditional，coig_pc，exam，finance这些转换麻烦或者语义上不适合当QA数据集的subset。 |
|
其中train_sft是全集，test_sft是ruozhiba，以便代码能够跑通。 |
|
|
|
经过reformat的本数据集可以直接使用[alignment-handbook](https://github.com/huggingface/alignment-handbook) 进行sft。 |
|
|
|
可以使用[zephyr-7b-beta/sft/config_qlora.yaml](https://github.com/huggingface/alignment-handbook/blob/main/recipes/zephyr-7b-beta/sft/config_qlora.yaml)进行尝试，模型和数据集都可以使用本地文件夹。 |
|
|
|
|
|
```bibtex |
|
@misc{bai2024coig, |
|
title={COIG-CQIA: Quality is All You Need for Chinese Instruction Fine-tuning}, |
|
author={Bai, Yuelin and Du, Xinrun and Liang, Yiming and Jin, Yonggang and Liu, Ziqiang and Zhou, Junting and Zheng, Tianyu and Zhang, Xincheng and Ma, Nuo and Wang, Zekun and others}, |
|
year={2024}, |
|
eprint={2403.18058}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.CL} |
|
} |
|
``` |
|
|
