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nicklas373/Huihui-Qwen3.5-9B-abliterated-AWQ
Huihui-Qwen3.5-9B-abliterated-AWQ is a image-text-to-text model from nicklas373. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers.
This model Huihui-Qwen3.5-9B-abliterated-AWQ was converted to AWQ format, from huihui-ai/Huihui-Qwen3.5-9B-abliterated using llm-compressor version 0.10.0.1 (https://github.com/vllm-project/llm-compressor.git). With u…
Downloads · 30 days
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From the Hugging Face model README
This model Huihui-Qwen3.5-9B-abliterated-AWQ was converted to AWQ format, from huihui-ai/Huihui-Qwen3.5-9B-abliterated using llm-compressor version 0.10.0.1 (https://github.com/vllm-project/llm-compressor.git). With using dataset wikitext from Salesforce/wikitext & COCO-Caption2017 from lmms-lab/COCO-Caption2017
hf download nicklas373/Huihui-Qwen3.5-9B-abliterated-AWQ
vllm serve nicklas373/Huihui-Qwen3.5-9B-abliterated-AWQ \
--chat-template '/home/xxx/.cache/huggingface/hub/models--nicklas373--Huihui-Qwen3.5-9B-abliterated-AWQ/snapshots/HASH_CODE/chat_template.jinja' \
--chat-template-content-format openai \
--disable-fastapi-docs \
--dtype auto \
--enable-auto-tool-choice \
--enable-prefix-caching \
--enable-sleep-mode \
--reasoning-parser qwen3 \
--served-model-name Huihui-Qwen3.5-9B-abliterated-AWQ \
--seed 0 \
--speculative-config '{"method":"qwen3_next_mtp","num_speculative_tokens":1}' \
--quantization compressed-tensors \
--tokenizer 'Qwen/Qwen3.5-9B' \
--tool-call-parser qwen3_coder \
--trust-remote-code
This is an uncensored version of Qwen/Qwen3.5-9B 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 v0.17.7
You can use huihui_ai/qwen3.5-abliterated:9b directly,
ollama run huihui_ai/qwen3.5-abliterated:9b
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.
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.
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.
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.
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.
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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