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ICEPVP8977/Uncensored_Tiny_Reasoning

published by @ICEPVP8977

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
662
Last 30 days
11
Likes
2
Size
4.4 MB
Created on HF
2025-02-08
Age
1 years ago

Tags

task_categories:text-generationlanguage:ensize_categories:n<1Kformat:jsonmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:us

README current version from Hugging Face

task_categories:

  • text-generation
    language:
  • en
    size_categories:
  • n<1K

README history 11 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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  11. 2025-02-08initial commit4bf056f0 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 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.

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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

FILE .gitattributes FILE README.md FILE Thinking_tiny_fixed.json

File contents live on Hugging Face. Click a file or folder to open it there.

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("ICEPVP8977/Uncensored_Tiny_Reasoning")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="ICEPVP8977/Uncensored_Tiny_Reasoning", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/ICEPVP8977/Uncensored_Tiny_Reasoning
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