p-e-w / Model details
gpt-oss-20b-heretic
p-e-w/gpt-oss-20b-heretic
About this model
p-e-w's decensored derivative of openai/gpt-oss-20b, created with Heretic v1.0.0. The creator describes it as a decensored version and lists abliteration parameters for attention and MLP projections. The model card reports a KL divergence of 0.96 and 58 out of 100 refusals, compared with 100 out of 100 for the original model; these figures are the creator's own reported measurements, not independently verified here. Weights are provided as safetensors under the Apache 2.0 license. The inherited OpenAI model card content about reasoning, tool use, and hardware requirements describes the base model and is not an evaluation of these modified weights.
Description sources
Source-based description, not an independent evaluation. Check the linked sources for the creator’s claims and limitations.
Size and formats
- Base model
- Unknown
- Parameters
- 20.9148B
- Main repository formats
- safetensors
- License tag
- apache-2.0
- Languages
- Unknown
- Last updated
- 2025-11-16 · 03:56:13.000 UTC
What changed
Model types are creator-reported, not independently tested. These labels describe source metadata, not a guarantee of behavior.
- abliteratedsource tag:
abliterated
- uncensoredsource tag:
uncensored
Family evidence
These groupings are source-reported. Explicit base identifiers take priority over generic architecture tags.
- gpt-oss: Family / architecture tag: gpt_oss
Available versions
Versions appear here only when they explicitly name this exact model as their source. Check each repository for available files.
- Main repository files ↗safetensors
- No other explicitly linked versions recorded.
Link to this listing
Made or quantized this model? Paste one of these into your model card or README so people can find this listing.
Markdown
[Listed on Custom Clankers](https://customclankers.com/models/p-e-w-gpt-oss-20b-heretic/)HTML
<a href="https://customclankers.com/models/p-e-w-gpt-oss-20b-heretic/">Listed on Custom Clankers</a>Plain text links only: no image, no script, nothing loaded from this site.
Customize or build on this model
Listed from public GitHub data, not tested by us. Read the code and license before you run anything.
Tools to customize it further
Remove more refusals
- Heretic ↗ ★ 36,365
Removes refusal behavior from transformer models automatically. It pairs directional ablation (abliteration) with an Optuna parameter search that tries to cut refusals while keeping the model close to the original, so you don't have to pick layers by hand.
- OBLITERATUS ↗ ★ 8,941
A larger refusal-removal toolkit with several abliteration methods, usable locally or through a hosted Hugging Face Space. Check the telemetry setting before you run it: the README describes telemetry as opt-in, but on by default in the Spaces version.
Fine-tune it on your own data
- Unsloth ↗ ★ 78,505
A desktop app and Python library for running and training models locally. Its README lists LoRA, QLoRA, full fine-tuning, DPO and GRPO, plus export to formats including GGUF, on Windows, Linux, WSL and macOS.
- LlamaFactory ↗ ★ 75,708
Fine-tunes more than 100 language and vision-language models from a command line or a browser-based Web UI, aimed at training without writing code.
Make a smaller download (quantize)
- llama.cpp ↗ ★ 132,209
Runs models locally and includes the tools behind most GGUF files. A conversion script turns Hugging Face weights into GGUF, and llama-quantize shrinks a high-precision GGUF to lower-bit formats, which can cost some accuracy.
- MLX LM ↗ ★ 7,461
Apple's MLX package for running and fine-tuning models on Apple silicon. It can quantize models and upload them to the Hugging Face Hub, and supports LoRA and full fine-tuning.
Merge it with another model
- mergekit ↗ ★ 7,414
Merges pretrained models with many merge methods. It works out-of-core, so merges can run on a CPU or with as little as 8 GB of VRAM, and it also handles LoRA extraction and mixture-of-experts merges.
Learn the techniques
- LLM Course ↗ ★ 84,653
A free course with roadmaps and Colab notebooks. Its notebooks include one-click tools for merging with MergeKit, quantizing to GGUF, GPTQ, EXL2, AWQ and HQQ, and automatic abliteration with custom datasets.
Source provenance
- Downloads
- 1,974
- Likes
- 152
- Metadata checked
- 2026-10-25 · 04:15:09 UTC
- First seen in index
- 2026-10-25 · 04:15:09 UTC
- Source revision
- 40a07b3c6d681a949db1ace3185050b5a0893093
Source-card excerpt
Source model card excerpt: This is a decensored version of openai/gpt-oss-20b, made using Heretic v1.0.0 Abliteration parameters Parameter Value :-------- :---: direction index 16.66 attn.o proj.max weight 1.44
From p-e-w/gpt-oss-20b-heretic. Creator model-card excerpt, not an independent review.
Inspect before you run
Low refusal is not proof of correctness. Outputs can be inaccurate, harmful, or biased. Review the model card, license and files yourself. A license tag is not commercial-use advice. Parameter counts are source metadata; no hardware compatibility is implied.
This directory does not host or redistribute model weights. Refusal profiles are measured by us on a fixed prompt set; all other behavior claims are source-reported.
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