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language:
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- en
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license: apache-2.0
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library_name:
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base_model:
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tags:
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- distillation
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- /think
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- chat
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- abliterated
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- uncensored
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extra_gated_prompt: >-
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**Usage Warnings**
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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.
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---
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# huihui-ai/Homunculus-abliterated
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This is an uncensored version of [arcee-ai/Homunculus](https://huggingface.co/arcee-ai/Homunculus) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more about it).
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This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens.
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language:
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- en
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license: apache-2.0
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library_name: exllamav2
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base_model:
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- huihui-ai/Homunculus-abliterated
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tags:
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- distillation
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- /think
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- chat
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- abliterated
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- uncensored
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---
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# Homunculus-abliterated-exl2
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Original model: [Homunculus-abliterated](https://huggingface.co/huihui-ai/Homunculus-abliterated) by [huihui.ai](https://huggingface.co/huihui-ai)
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Based on: [Homunculus](https://huggingface.co/arcee-ai/Homunculus) by [Arcee AI](https://huggingface.co/arcee-ai)
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Foundation model: [Mistral-Nemo-Base-2407](https://huggingface.co/mistralai/Mistral-Nemo-Base-2407) by [Mistral AI](https://huggingface.co/mistralai) with data and tokenizer from [Qwen3-235B-A22B](https://huggingface.co/Qwen/Qwen3-235B-A22B) by [Qwen](https://huggingface.co/Qwen)
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## Quants
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[4bpw h6 (main)](https://huggingface.co/cgus/Homunculus-abliterated-exl2/tree/main)
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[4.5bpw h6](https://huggingface.co/cgus/Homunculus-abliterated-exl2/tree/4.5bpw-h6)
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[5bpw h6](https://huggingface.co/cgus/Homunculus-abliterated-exl2/tree/5bpw-h6)
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[6bpw h6](https://huggingface.co/cgus/Homunculus-abliterated-exl2/tree/6bpw-h6)
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[8bpw h8](https://huggingface.co/cgus/Homunculus-abliterated-exl2/tree/8bpw-h8)
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## Quantization notes
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Made with Exllamav2 0.3.1 with default dataset.
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These quants can be used with RTX GPU on Windows or RTX/ROCm GPU on Linux with TabbyAPI or Text-Generation-WebUI.
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Exllamav2 quants must fully fit your GPU to be usable or to maintain maximum performance.
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For example, I use Mistral-Nemo-12B models with RTX3060/12GB 6bpw quant and 16k context (Q6 cache) or RTX4060TI/16GB with 6bpw 32k (Q8 cache).
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# Original model card.
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# huihui-ai/Homunculus-abliterated
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This is an uncensored version of [arcee-ai/Homunculus](https://huggingface.co/arcee-ai/Homunculus) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more about it).
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This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens.
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