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jtatman/stable-diffusion-prompts-uncensored

published by @jtatman

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
2.6K
Last 30 days
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Likes
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Size
150.1 MB
Created on HF
2024-01-04
Age
2 years ago

Description

Dataset Card for "stable-diffusion-prompts-uncensored"

Not SAFE for public - Definately Unfiltered

This dataset comes from prompts shared from images' metadata on Civitai. Not for the faint of heart.

Thanks to Civitai.com for all the models, building a playground, allowing fine tuning of models, and generally being a good influence on model building and generation.

The purpose of this dataset is to allow for analysis of prompts and feature analysis in prompts and… See the full description on the dataset page: https://huggingface.co/datasets/jtatman/stable-diffusion-prompts-uncensored.

Tags

task_categories:text-to-imagetask_categories:image-to-imagelanguage:enlicense:mitsize_categories:100K<n<1Mformat:parquetmodality:textlibrary:datasetslibrary:dasklibrary:mlcroissantlibrary:polarsregion:usuncensorednsfwartnot-for-all-audiencesdiffusersimage generation

README current version from Hugging Face


language:

  • en
    license: mit
    size_categories:
  • 100K<n<1M
    task_categories:
  • text-to-image
  • image-to-image
    pretty_name: NSFW Prompts
    dataset_info:
    features:
    • name: model
      dtype: string
    • name: prompt
      dtype: string
    • name: negative_prompt
      dtype: string
    • name: index_level_0
      dtype: int64
      splits:
    • name: train
      num_bytes: 647548943
      num_examples: 851568
      download_size: 0
      dataset_size: 647548943
      configs:
  • config_name: default
    data_files:
    • split: train
      path: data/train-*
      tags:
  • uncensored
  • nsfw
  • art
  • not-for-all-audiences
  • diffusers
  • image generation

Dataset Card for "stable-diffusion-prompts-uncensored"

Not SAFE for public - Definately Unfiltered

This dataset comes from prompts shared from images' metadata on Civitai. Not for the faint of heart.
Thanks to Civitai.com for all the models, building a playground, allowing fine tuning of models, and generally being a good influence on model building and generation.

The purpose of this dataset is to allow for analysis of prompts and feature analysis in prompts and negative prompts.

This could be for:

  • similarity
  • effective prompting
  • prompt alignment or misalignment
  • statistical research on prompts and categories
  • popularity of image generation approaches
  • mimimalism prompts with certain models
  • matching generated prompts to images for LLAVA purposes
  • mimimizing prompts for better context usage
  • social research on interest level and creative approaches
  • modeling based on prompts for automating prompt generation strategy
  • modeling of categorical interest and similarity
  • modeling of evolution of prompts based on model versioning

A seperate upload will include metadata statistics such as cry count, laugh count, etc. for semantic analysis based on prompt length and content.

README history 8 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. 2024-01-04Upload README.md with huggingface_hubd6cc36e1.8 KB
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  2. 2024-01-04Upload README.md with huggingface_hub8c194a91.8 KB
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  3. 2024-01-04updated metadata8a8755d1.8 KB
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  4. 2024-01-04Update README.md55994b01.8 KB
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  5. 2024-01-04Upload README.md with huggingface_hub064b3a3596 B
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  6. 2024-01-04Upload data/train-00001-of-00002-519ce29cb2488b50.parquet with huggingface_huba6ec3000 B
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  7. 2024-01-04Upload data/train-00000-of-00002-6bb4abc55af9e1bb.parquet with huggingface_hub49282d20 B
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  8. 2024-01-04initial commit4481c630 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 3 threads · 2 open · 3 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. 2026-02-23Newclosed1 💬#3
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  2. 2024-12-28[bot] Conversion to Parquetopen1 💬#2
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  3. 2024-05-23PRUpdate README.mdopen1 💬#1
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Metadata

License
mit

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("jtatman/stable-diffusion-prompts-uncensored")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="jtatman/stable-diffusion-prompts-uncensored", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/jtatman/stable-diffusion-prompts-uncensored
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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.

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