datasets:

• Salesforce/wikitext
• lmms-lab/COCO-Caption2017
  base_model:
• huihui-ai/Huihui-Qwen3.5-9B-abliterated
  pipeline_tag: image-text-to-text
  library_name: transformers
  tags:
• abliterated
• uncensored

Huihui-Qwen3.5-9B-abliterated-AWQ

Model Highlights

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

Datasets:

• Salesforce/wikitext
• lmms-lab/COCO-Caption2017

Base Model:

• huihui-ai/Huihui-Qwen3.5-9B-abliterated

Use with VLLM

1. Download models at first by using hf

      hf download nicklas373/Huihui-Qwen3.5-9B-abliterated-AWQ
   

2. Copy hash for snapshots directory, then use it for chat templates and tool call parser
   ex: /home/xxx/.cache/huggingface/hub/models--nicklas373--Huihui-Qwen3.5-9B-abliterated-AWQ/snapshots/HASH_CODE/xxx
3. Run models with this command

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

huihui-ai/Huihui-Qwen3.5-9B-abliterated

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.

ollama

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

Usage Warnings

• 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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