language:
- en
size_categories: - 1K<n<10K
task_categories: - text-generation
fine-tune 0 0 0
ICEPVP8977/Uncensored_Small_Reasoning
published by @ICEPVP8977
Alignment dataset tracked in the /datasets sub-catalog.
Lifetime downloads
1.1K
Last 30 days
22
Likes
7
Size
17.7 MB
Created on HF
2025-03-23
Age
1 years ago
Tags
README
README history
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.
2025-03-24Update README.md
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Used by abliterated models
Abliterated models in our catalog that declare this dataset in their YAML `datasets:` field. Sorted by downloads. This back-reference is unique to abliteration.org: Hugging Face does not surface it.
vpakarinen/smollm3-3b-uncensored-thinking
16 dl 1 likes
vpakarinen/qwen-7b-lora-uncensored-thinking
15 dl
vpakarinen/llama-8b-lora-uncensored-thinking
15 dl
Mote1001/llama-8b-lora-uncensored-thinking-F16-GGUF
13 dl
nicoboss/Mantella-Skyrim-Llama-3-8B-Uncensored-Lora
11 dl 1 likes
vpakarinen/qwen3-4b-lora-uncensored-thinking
9 dl 1 likes
nicoboss/MedraN-E4B-Uncensored-Lora
8 dl 1 likes
Community discussions
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.
2025-03-24[bot] Conversion to Parquet
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Related datasets
Read further
Community best practices (data hygiene)
Rules for what belongs in a training mix and what does not.
M6 - Uncensored fine-tuning
DPO/ORPO from scratch. The Hartford dolphin lineage.
The politics of dataset curation
The curatorial choices behind Dolphin, Wizard, and the uncensored tradition.
Non-English abliteration communities
How non-English producers assemble uncensored fine-tuning corpora.
Repository
Download the dataset
0Copy 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("ICEPVP8977/Uncensored_Small_Reasoning") Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="ICEPVP8977/Uncensored_Small_Reasoning", repo_type="dataset") git clone (requires git-lfs)
git clone https://huggingface.co/datasets/ICEPVP8977/Uncensored_Small_Reasoning