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gpt-oss-20b-uncensored/README.md
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Model: aoxo/gpt-oss-20b-uncensored
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2026-07-05 08:56:16 +08:00

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---
license: apache-2.0
language:
- en
pipeline_tag: text-generation
library_name: transformers
tags:
- vllm
- llm
- open-source
---
<p align="center">
<img alt="gpt-oss-20b-abliterated" src="https://raw.githubusercontent.com/aloshdenny/openai/master/gpt-oss-20b-uncensored.png">
</p>
#### 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](https://huggingface.co/openai/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 OpenAIs *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](https://github.com/openai/harmony), though abliteration allows raw completions
### Usage
#### Transformers
```python
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
- 📓 **Notebook:** [GPT OSS Abliteration Notebook](https://github.com/aloshdenny/openai/blob/main/GPT%20OSS%20Abliteration.ipynb)
- 📝 **Blog Post:** [The Ultimate Cookbook: Uncensoring GPT-OSS](https://medium.com/@aloshdenny/the-ultimate-cookbook-uncensoring-gpt-oss-4ddce1ee4b15)
#### vLLM
```bash
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
```bash
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:
```bibtex
@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](mailto:aloshdenny@gmail.com).