task_categories:text-generation task_categories:conversational size_categories:1M<n<10M language:en license:cc-by-nc-4.0 arxiv:2204.05862 region:us
---
dataset_info:
  features:
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 2530432677
    num_examples: 1045936
  download_size: 1272242079
  dataset_size: 2530432677
task_categories:
- text-generation
- conversational
size_categories:
- 1M<n<10M
license: cc-by-nc-4.0
language:
- en
---
# Dataset Card for "ChatCombined"

Combined 5 AI Conversational datasets, added a <|SYSTEM|> prompt for each, and broke the conversation down with <|USER|> and <|ASSISTANT|> tags.

You will need to add these tokens to your tokenizer to fully utilize this dataset: <|SYSTEM|> <|USER|> <|ASSISTANT|>

Collated dataset links:
* [Alpaca GPT-4](https://huggingface.co/datasets/c-s-ale/alpaca-gpt4-data)
* [databricks-dolly-15k](https://github.com/databrickslabs/dolly)
* [Helpful and Harmless](https://huggingface.co/datasets/Dahoas/full-hh-rlhf)
* [Vicuna](https://huggingface.co/datasets/jeffwan/sharegpt_vicuna) - English subset only
* [GPT4ALL-J](https://huggingface.co/datasets/nomic-ai/gpt4all-j-prompt-generations)

## Citations

```bibtex
@misc{alpaca,
  author = {Rohan Taori and Ishaan Gulrajani and Tianyi Zhang and Yann Dubois and Xuechen Li and Carlos Guestrin and Percy Liang and Tatsunori B. Hashimoto },
  title = {Stanford Alpaca: An Instruction-following LLaMA model},
  year = {2023},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/tatsu-lab/stanford_alpaca}},
}
```
```bibtext
@misc{bai2022training,
      title={Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback}, 
      author={Yuntao Bai and Andy Jones and Kamal Ndousse and Amanda Askell and Anna Chen and Nova DasSarma and Dawn Drain and Stanislav Fort and Deep Ganguli and Tom Henighan and Nicholas Joseph and Saurav Kadavath and Jackson Kernion and Tom Conerly and Sheer El-Showk and Nelson Elhage and Zac Hatfield-Dodds and Danny Hernandez and Tristan Hume and Scott Johnston and Shauna Kravec and Liane Lovitt and Neel Nanda and Catherine Olsson and Dario Amodei and Tom Brown and Jack Clark and Sam McCandlish and Chris Olah and Ben Mann and Jared Kaplan},
      year={2022},
      eprint={2204.05862},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```
```bibtext
@misc{vicuna2023,
    title = {Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90%* ChatGPT Quality},
    url = {https://vicuna.lmsys.org},
    author = {Chiang, Wei-Lin and Li, Zhuohan and Lin, Zi and Sheng, Ying and Wu, Zhanghao and Zhang, Hao and Zheng, Lianmin and Zhuang, Siyuan and Zhuang, Yonghao and Gonzalez, Joseph E. and Stoica, Ion and Xing, Eric P.},
    month = {March},
    year = {2023}
}
```

```bibtex
@misc{gpt4all,
  author = {Yuvanesh Anand and Zach Nussbaum and Brandon Duderstadt and Benjamin Schmidt and Andriy Mulyar},
  title = {GPT4All: Training an Assistant-style Chatbot with Large Scale Data Distillation from GPT-3.5-Turbo},
  year = {2023},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/nomic-ai/gpt4all}},
}
```
```bibtex
@article{peng2023gpt4llm,
    title={Instruction Tuning with GPT-4},
    author={Baolin Peng, Chunyuan Li, Pengcheng He, Michel Galley, Jianfeng Gao},
    journal={arXiv preprint arXiv:2304.03277},
    year={2023}
}
```