library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen3-Coder-480B-A35B-Instruct/blob/main/LICENSE
pipeline_tag: text-generation
base_model:
- Qwen/Qwen3-Coder-480B-A35B-Instruct
tags: - chat
- abliterated
- uncensored
- GGUF
extra_gated_prompt: >-
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.
huihui-ai/Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-GGUF
This is an uncensored version of Qwen/Qwen3-Coder-480B-A35B-Instruct 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
You can use huihui_ai/qwen3-coder-abliterated:480b-a35b-instruct-q3_K_M directly,
ollama run huihui_ai/qwen3-coder-abliterated:480b-a35b-instruct-q3_K_M --verbose
huihui_ai/qwen3-coder-abliterated:480b-a35b-instruct-q4_K_M
ollama run huihui_ai/qwen3-coder-abliterated:480b-a35b-instruct-q4_K_M --verbose
Download and merge
Important update: Since the previously uploaded Q4_K_M chat template was not compatible with the Opencode tool, we have deleted it. Therefore, we have modified the chat template and are now uploading the Q2_K version, which can be used on Opencode.
Use the llama.cpp split program to merge model (llama-gguf-split needs to be compiled.),
huggingface-cli download huihui-ai/Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-GGUF --local-dir ./huihui-ai/Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-GGUF --token xxx
llama-gguf-split --merge huihui-ai/Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-GGUF/Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-Q2_K-00001-of-00019.gguf huihui-ai/Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-GGUF/Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-Q2_K.gguf
Tool Calling
By using llama-serve and the opencode test tool to test calls, it is evident that the performance is excellent.
llama-server -m huihui-ai/Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-GGUF/Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-Q2_K.gguf --port 8080 --host 0.0.0.0 -c 262144
The following are the relevant configurations for openconde.json used in a Docker environment.
{
"$schema": "https://opencode.ai/config.json",
"provider": {
"llama-server": {
"npm": "@ai-sdk/openai-compatible",
"name": "llama-server",
"options": {
"baseURL": "http://host.docker.internal:8080/v1"
},
"models": {
"Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-Q2_K": {
"name": "Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-Q2_K",
"tools": true,
"reasoning": true,
"options": {
"num_ctx": 32768
}
}
}
}
}
}
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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