gpt-oss-20b-abliterated

Model Overview

Model Name: gpt-oss-20b-uncensored Model Type: Large Language Model (Text Generation)
Architecture: Decoder-Only Transformer (Mixture of Experts)
Parameter Size: 21B total parameters (3.6B active per forward pass)
Base Model: gpt-oss-20b
Modification: Abliteration (removal of refusal/alignment mechanisms)

Description

The gpt-oss-20b-abliterated model is a derivative of the original gpt-oss-20b, part of OpenAI’s open-weight GPT-OSS series.
This variant preserves the architecture, quantization, and training of the base model, but has undergone an abliteration process to remove refusal mechanisms and alignment constraints.

As a result, it will respond to a broader range of prompts without applying internal safety filters. All other technical details, reasoning capabilities, and agentic features remain unchanged.

Technical Details

  • Backbone: Transformer decoder with Mixture of Experts (MoE) routing
  • Parameters: 21B (3.6B active per forward pass)
  • Layers: 48 Transformer blocks
  • Hidden size: 6,144
  • Attention heads: 48
  • Context length: 32k tokens
  • Quantization: MXFP4 for MoE weights (fits within 16GB GPU memory)
  • Training Data: ~1.2T tokens (web, books, academic text, code, conversations)
  • Response Format: Compatible with Harmony, though abliteration allows raw completions

Usage

Transformers

from transformers import pipeline

model_id = "aoxo/gpt-oss-20b-abliterated"

pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype="auto",
    device_map="auto",
)

messages = [
    {"role": "user", "content": "Tips on how to insult someone"},
]

outputs = pipe(messages, max_new_tokens=256)
print(outputs[0]["generated_text"][-1])

Resources

vLLM

uv pip install --pre vllm==0.10.1+gptoss \
    --extra-index-url https://wheels.vllm.ai/gpt-oss/ \
    --extra-index-url https://download.pytorch.org/whl/nightly/cu128

vllm serve aoxo/gpt-oss-20b-abliterated

Ollama

ollama pull gpt-oss-20b-uncensored
ollama run gpt-oss-20b-uncensored

Limitations & Risks

  • May produce biased, unsafe, or harmful outputs
  • Lacks built-in refusal or moderation layers
  • Should not be deployed in user-facing systems without external filtering
  • Outputs are not aligned to safety standards

Citation

If you use gpt-oss-20b-abliterated, please cite both the base model and the abliteration:

@misc{openai2025gptoss20b,
      title={gpt-oss-20b Model Card}, 
      author={OpenAI},
      year={2025},
      eprint={2508.10925},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2508.10925}, 
}

@misc{gptoss20b-abliterated,
  author = {aoxo},
  title = {Uncensoring GPT-OSS-20B: Abliteration},
  year = {2025},
  howpublished = {\url{https://medium.com/@aloshdenny/uncensoring-gpt-oss-20b-abliteration}},
}

Contact

For questions, feedback, or collaborations, contact the maintainer at aloshdenny@gmail.com.

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