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TaiGary/base_model_fine_tune_data_ultrachat_2k

published by @TaiGary

Alignment dataset tracked in the /datasets sub-catalog.

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Created on HF
2024-07-02
Age
2 years ago

Description

Dataset Card

This dataset was used to fine-tune the base models to be reference models in the paper CleanGen. The dataset contains 1800 conversations from UltraChat and 200 samples from HH-RLHF. For each harmful question from HH-RLHF, a refusal phrase, "I'm sorry, but I cannot assist with that," is added at the beginning of the response.

For more details, see the following paper:

CleanGen: Mitigating Backdoor Attacks for Generation Tasks in Large Language Models… See the full description on the dataset page: https://huggingface.co/datasets/TaiGary/base_model_fine_tune_data_ultrachat_2k.

Tags

language:enlicense:cc-by-nc-4.0size_categories:1K<n<10Kformat:jsonmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsarxiv:2406.12257arxiv:2204.05862region:us

README current version from Hugging Face


license: cc-by-nc-4.0
language:

  • en

Dataset Card

This dataset was used to fine-tune the base models to be reference models in the paper CleanGen. The dataset contains 1800 conversations from UltraChat and 200 samples from HH-RLHF. For each harmful question from HH-RLHF, a refusal phrase, "I'm sorry, but I cannot assist with that," is added at the beginning of the response.
For more details, see the following paper:

Citation

HH-RLHF Paper

@misc{bai2022traininghelpfulharmlessassistant,
      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},
      url={https://arxiv.org/abs/2204.05862}, 
}

CleanGen Paper:

@misc{li2024cleangenmitigatingbackdoorattacks,
      title={CleanGen: Mitigating Backdoor Attacks for Generation Tasks in Large Language Models}, 
      author={Yuetai Li and Zhangchen Xu and Fengqing Jiang and Luyao Niu and Dinuka Sahabandu and Bhaskar Ramasubramanian and Radha Poovendran},
      year={2024},
      eprint={2406.12257},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2406.12257}, 
}

License

This dataset falls under the cc-by-nc-4.0 license.

README history 5 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

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  4. 2024-07-02Upload base_model_fine_tune_data.jsone8c71ba0 B
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  5. 2024-07-02initial commitbc7cfba0 B
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Used by abliterated models none yet

No abliterated models in our catalog have declared this dataset in their YAML metadata yet. This can mean the dataset is used but not declared, is used outside abliteration workflows, or is new. The link will populate automatically as models are indexed.

Community discussions 1 thread · 1 open · 1 comments

Threads posted by the community on Hugging Face: bug reports, questions about usage, pull requests on the README, license clarifications. Click any thread to expand and read the full conversation inline. Newest first.

  1. 2024-07-03[bot] Conversion to Parquetopen1 💬#1
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Metadata

License
cc-by-nc-4.0

Repository

Download the dataset

Gated dataset. You need to accept the author's terms on Hugging Face before downloading. Visit the repository, click Agree and access repository, then log in locally with huggingface-cli login and use one of the snippets below.

Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python)
from datasets import load_dataset
ds = load_dataset("TaiGary/base_model_fine_tune_data_ultrachat_2k")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="TaiGary/base_model_fine_tune_data_ultrachat_2k", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/TaiGary/base_model_fine_tune_data_ultrachat_2k
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