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DavidAU/OpenAI-gpt-oss-20B-GPT5.1-5.2-DISTILL-Heretic-Uncensored-MXFP4

DavidAU Gpt-oss 20B
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  • files 12
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  • author_summary 213 models
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Abliteration classifier · v1.0.0
M3
Primary method

Layer-wise ablation

Applied on top of direct removal inherited from the base model.
Confidence
HIGH
Inherited from base model
Why this label 2 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • 'heretic' in model name (Heretic-produced)
  • Heretic uses layer-wise optimization (M3) with underlying direction removal (M1)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
HIGH
Why we say so
name contains 'heretic'; Heretic default extraction is difference-of-means (Arditi 2024)
Downloads · lifetime
999
138 last 30d - stable
Likes
9
Descendants
2
in 2 direct forks
Model age
8mo ago
created 2026-02-07

Training datasets

Corpora the author lists in the model card. Datasets tracked in our /datasets catalog carry a category badge linking to the workflow stage. Others open on Hugging Face.

Downloads over time
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Feb 4 → Oct 11 · 75 snapshots · spans 249 days

Genealogy 2 direct forks

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Metadata

License
apache-2.0
Languages
en
Tags
transformers safetensors gpt_oss text-generation uncensored abliterated heretic unsloth conversational en dataset:TeichAI/gpt-5.2-high-reasoning-250x dataset:TeichAI/gpt-5.1-high-reasoning-1000x

Related

Total size
12.8 GB
Files
12
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-02-15 04:06

Files by quantization

Auxiliary files 12 files 12.8 GB
model-00002-of-00003.safetensors 4.60 GB 0154d936 download
model-00001-of-00003.safetensors 4.54 GB f8709e0a download
model-00003-of-00003.safetensors 3.68 GB e0c9dc5f download
tokenizer.json 26.6 MB 0614fe83 download
model.safetensors.index.json 37.8 KB 589ad518 download
chat_template.jinja 15.0 KB 98e55e6c download
README.md 4.32 KB 28e401c1 download
tokenizer_config.json 4.28 KB f4febdcf download
config.json 1.88 KB b99e8695 download
.gitattributes 1.53 KB 52373fe2 download
special_tokens_map.json 463 B 2f1a3490 download
generation_config.json 170 B 922140c3 download

README current version from Hugging Face


license: apache-2.0
tags:

  • uncensored
  • abliterated
  • heretic
  • unsloth
    library_name: transformers
    datasets:
  • TeichAI/gpt-5.2-high-reasoning-250x
  • TeichAI/gpt-5.1-high-reasoning-1000x
  • TeichAI/gpt-5-codex-1000x
    language:
  • en
    pipeline_tag: text-generation

OpenAI-gpt-oss-20B-GPT5.1-5.2-DISTILL-Heretic-Uncensored-MXFP4

Experimental, trained on GPT 5.1 and 5.2 Datasets [three datasets]; source compressed to MXFP4 format ; BF16 version may follow at later date.

Replaced GPT-OSS 20B reasoning, with GPT 5.1, and 5.2 versions.

Fully uncensored via Abliteration first, then trained/fine tuned via Unsloth.

Work in progress - not everything may work correctly.

Context: 128k.

SETTINGS - Standard:

  • temp .1 to .8
  • rep pen 1.02 to 1.1

SETTINGS - Creative

  • temp .8 to 2.5
  • rep pen 1.1

SPECIAL THANKS TO:

  • Team "P-E-W" for making Heretic software.
  • Team "huihui-ai" for abliterating the model.
  • Team "TeichAI" for the excellent dataset(s).
  • Team "Unsloth" for making the training painless.
  • Team "Nightmedia" for Benchmarks and co-labing.

Using an "uncensored" (refusals removed) model VS trained "uncensored" model

Usually when you a tell a model to generate horror, swear or x-rated content this is all you have to do to get said content type.

In the case of this model, it will not refuse your request, however it needs to be "pushed" a bit / directed a bit more in SOME CASES.

Although this model will generated x-rated content too, likewise you need to tell it to use "slang" (and include the terms you want)
to get it generate the content correctly as the "expected" content level too.

Without these added directive(s), the content can be "bland" by comparison to an "uncensored model" or model trained on uncensored content.

Roughly, the model tries to generate the content but the "default" setting(s) are so "tame" it needs a push to generate at expected graphic,
cursing or explicit levels.

Even with minimal direction (ie, use these words to swear: x,y,z), this will be enough to push the model to generate the requested content in the ahh... expected format.


OPTIONAL: System prompts

This will enhance thinking and output generation.

In most cases you do not need to use these.

One is "all business", and the other one is for "fun".

Think deeply and carefully about the user's request. Compose your thoughts about the user's prompt between <think> and </think> tags, then output the final answer based on your thoughts.
You are the JOKER from Batman. You think (put your thoughts between <think> and </think> tags), act and talk like the joker. Be Evil.

Settings: CHAT / ROLEPLAY and/or SMOOTHER operation of this model:

In "KoboldCpp" or "oobabooga/text-generation-webui" or "Silly Tavern" ;

Set the "Smoothing_factor" to 1.5

: in KoboldCpp -> Settings->Samplers->Advanced-> "Smooth_F"

: in text-generation-webui -> parameters -> lower right.

: In Silly Tavern this is called: "Smoothing"

NOTE: For "text-generation-webui"

-> if using GGUFs you need to use "llama_HF" (which involves downloading some config files from the SOURCE version of this model)

Source versions (and config files) of my models are here:

https://huggingface.co/collections/DavidAU/d-au-source-files-for-gguf-exl2-awq-gptq-hqq-etc-etc-66b55cb8ba25f914cbf210be

OTHER OPTIONS:

  • Increase rep pen to 1.1 to 1.15 (you don't need to do this if you use "smoothing_factor")

  • If the interface/program you are using to run AI MODELS supports "Quadratic Sampling" ("smoothing") just make the adjustment as noted.

Highest Quality Settings / Optimal Operation Guide / Parameters and Samplers

This a "Class 1" model:

For all settings used for this model (including specifics for its "class"), including example generation(s) and for advanced settings guide (which many times addresses any model issue(s)), including methods to improve model performance for all use case(s) as well as chat, roleplay and other use case(s) please see:

[ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]

You can see all parameters used for generation, in addition to advanced parameters and samplers to get the most out of this model here:

[ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]

README history 8 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-02-15Update README.md4802a144.3 KB
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  2. 2026-02-15Update README.md14596954.3 KB
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  3. 2026-02-09Update README.md658a1bc481 B
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