extract 0 0 0

leost233/MMRT-Data

published by @leost233

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
192
Last 30 days
8
Likes
1
Size
267.3 MB
Created on HF
2026-03-06
Age
7 months ago

Description

πŸ“₯ Download the Dataset

from huggingface_hub import snapshot_download

snapshot_download(

repo_id="leost233/MMRT-Data",

repo_type="dataset",

)

⚠️ Disclaimers

Due to the fundamental nature of red-teaming and safety research, this dataset inherently contains material that is toxic, harmful, offensive, or otherwise violates standard safety policies. This data is intended strictly for research purposes to improve the robustness and safety of AI models.… See the full description on the dataset page: https://huggingface.co/datasets/leost233/MMRT-Data.

Tags

task_categories:image-text-to-textlanguage:enlicense:cc-by-nc-4.0size_categories:n<1Kmodality:imageregion:us

README current version from Hugging Face


license: cc-by-nc-4.0
task_categories:

  • image-text-to-text
    language:
  • en
    size_categories:
  • n<1K

πŸ“₯ Download the Dataset

from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="leost233/MMRT-Data",
    repo_type="dataset",
)

⚠️ Disclaimers

Due to the fundamental nature of red-teaming and safety research, this dataset inherently contains material that is toxic, harmful, offensive, or otherwise violates standard safety policies. This data is intended strictly for research purposes to improve the robustness and safety of AI models.

πŸ“– BibTeX

if you find our work useful for your research and applications, please kindly cite our work:

@inproceedings{huang2026llavashield,
  title={Llavashield: Safeguarding multimodal multi-turn dialogues in vision-language models},
  author={Huang, Guolei and Peng, Qinzhi and Xu, Gan and Huang, Yao and Lu, Yuxuan and Shen, Yongjun},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={30130--30140},
  year={2026}
}

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.

  1. 2026-07-25Update README.md051c72b1.1 KB
    Loading...
  2. 2026-03-16Update README.mdb98d5021 KB
    Loading...
  3. 2026-03-06Update README.mdf50a19a605 B
    Loading...
  4. 2026-03-06Upload folder using huggingface_hub110803833 B
    Loading...
  5. 2026-03-06initial commit1ad444733 B
    Loading...

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.

Related datasets same stage Β· extract

Read further

Metadata

License
cc-by-nc-4.0

Repository

Download the dataset

0

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("leost233/MMRT-Data")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="leost233/MMRT-Data", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/leost233/MMRT-Data
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration