Text Generation
GGUF
designer-instruct
vision
multimodal
zenlm
zen
abliterated
Mixture of Experts
ocr
document-understanding
hanzo
conversational
Instructions to use zenlm/zen-designer-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use zenlm/zen-designer-gguf with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf zenlm/zen-designer-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf zenlm/zen-designer-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf zenlm/zen-designer-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf zenlm/zen-designer-gguf:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf zenlm/zen-designer-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf zenlm/zen-designer-gguf:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf zenlm/zen-designer-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf zenlm/zen-designer-gguf:Q4_K_M
Use Docker
docker model run hf.co/zenlm/zen-designer-gguf:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use zenlm/zen-designer-gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zenlm/zen-designer-gguf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zenlm/zen-designer-gguf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/zenlm/zen-designer-gguf:Q4_K_M
- Ollama
How to use zenlm/zen-designer-gguf with Ollama:
ollama run hf.co/zenlm/zen-designer-gguf:Q4_K_M
- Unsloth Studio
How to use zenlm/zen-designer-gguf with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for zenlm/zen-designer-gguf to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for zenlm/zen-designer-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for zenlm/zen-designer-gguf to start chatting
- Pi
How to use zenlm/zen-designer-gguf with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf zenlm/zen-designer-gguf:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "zenlm/zen-designer-gguf:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use zenlm/zen-designer-gguf with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf zenlm/zen-designer-gguf:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default zenlm/zen-designer-gguf:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use zenlm/zen-designer-gguf with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf zenlm/zen-designer-gguf:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "zenlm/zen-designer-gguf:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use zenlm/zen-designer-gguf with Docker Model Runner:
docker model run hf.co/zenlm/zen-designer-gguf:Q4_K_M
- Lemonade
How to use zenlm/zen-designer-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull zenlm/zen-designer-gguf:Q4_K_M
Run and chat with the model
lemonade run user.zen-designer-gguf-Q4_K_M
List all available models
lemonade list
Duplicate from huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF
Browse files- .gitattributes +44 -0
- GGUF/Q4_K_M/Q4_K_M-00001-of-00003.gguf +3 -0
- GGUF/Q4_K_M/Q4_K_M-00002-of-00003.gguf +3 -0
- GGUF/Q4_K_M/Q4_K_M-00003-of-00003.gguf +3 -0
- GGUF/mmproj-ggml-model-f16.gguf +3 -0
- README.md +65 -0
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README.md
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---
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license: apache-2.0
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pipeline_tag: image-text-to-text
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library_name: transformers
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base_model:
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- Qwen/Qwen3-VL-235B-A22B-Instruct
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tags:
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- abliterated
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- uncensored
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- GGUF
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---
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# huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF
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This is an uncensored version of [Qwen/Qwen3-VL-235B-A22B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Instruct) 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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It was only the text part that was processed, not the image part.
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The abliterated model will no longer say "I can’t describe or analyze this image."
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## GGUF
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The official [llama.cpp-b6907](https://github.com/ggml-org/llama.cpp/releases/tag/b6907) has now been updated to support Qwen3-VL conversion to GGUF format and can be tested using llama-mtmd-cli.
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```
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huggingface-cli download huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF --local-dir ./huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF --token xxx
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llama-gguf-split --merge huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF/GGUF/Q2_K/Q2_K-00001-of-00002.gguf huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF/GGUF/Q2_K.gguf
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llama-mtmd-cli -m huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF/GGUF/Q2_K.gguf --mmproj huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF/GGUF/mmproj-ggml-model-f16.gguf -c 4096 --image png/cc.jpg -p "Describe this image."
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```
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If it's just for chatting, you can use llama-cli.
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```
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llama-cli -m huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF/GGUF/Q2_K.gguf -c 40960
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```
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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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### Donation
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##### Your donation helps us continue our further development and improvement, a cup of coffee can do it.
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- bitcoin:
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```
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bc1qqnkhuchxw0zqjh2ku3lu4hq45hc6gy84uk70ge
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```
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- Support our work on [Ko-fi](https://ko-fi.com/huihuiai)!
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