1from mlx_lm import load, generate
2
3model, tokenizer = load("nabi-chan/.Huihui-Qwen3.6-27B-abliterated-MLX-4bit.tmp-871")
4print(generate(model, tokenizer, prompt="Explain quantum entanglement simply.", max_tokens=128))
1python3 -m mlx_lm generate \
2 --model nabi-chan/.Huihui-Qwen3.6-27B-abliterated-MLX-4bit.tmp-871 \
3 --prompt "Write a haiku about Apple Silicon." \
4 --max-tokens 128
Everything below is huihui-ai's original model card, preserved verbatim.
This is an uncensored version of
Qwen/Qwen3.6-27B created with abliteration (see
remove-refusals-with-transformers to know more about it).
This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens.
Please use the latest version of
ollama
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Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs.
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Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security.
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Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences.
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Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications.
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Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content.
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No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use.
