Instructions to use laichaoyi/MixupModels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use laichaoyi/MixupModels with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="laichaoyi/MixupModels", filename="text_encoders/anima/Qwen3-0.6B-Base.Q8.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use laichaoyi/MixupModels 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 laichaoyi/MixupModels:Q4_K_M # Run inference directly in the terminal: llama cli -hf laichaoyi/MixupModels:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf laichaoyi/MixupModels:Q4_K_M # Run inference directly in the terminal: llama cli -hf laichaoyi/MixupModels: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 laichaoyi/MixupModels:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf laichaoyi/MixupModels: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 laichaoyi/MixupModels:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf laichaoyi/MixupModels:Q4_K_M
Use Docker
docker model run hf.co/laichaoyi/MixupModels:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use laichaoyi/MixupModels with Ollama:
ollama run hf.co/laichaoyi/MixupModels:Q4_K_M
- Unsloth Studio
How to use laichaoyi/MixupModels 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 laichaoyi/MixupModels 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 laichaoyi/MixupModels to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for laichaoyi/MixupModels to start chatting
- Pi
How to use laichaoyi/MixupModels with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf laichaoyi/MixupModels: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": "laichaoyi/MixupModels:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use laichaoyi/MixupModels with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf laichaoyi/MixupModels: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 laichaoyi/MixupModels:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use laichaoyi/MixupModels with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf laichaoyi/MixupModels: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 "laichaoyi/MixupModels: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 laichaoyi/MixupModels with Docker Model Runner:
docker model run hf.co/laichaoyi/MixupModels:Q4_K_M
- Lemonade
How to use laichaoyi/MixupModels with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull laichaoyi/MixupModels:Q4_K_M
Run and chat with the model
lemonade run user.MixupModels-Q4_K_M
List all available models
lemonade list
Upload models.json
Browse files- models.json +2 -175
models.json
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"type": "Others",
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"thumbnail": "https://i.ibb.co/msQPWSQ/sam3.jpg",
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"url": "https://huggingface.co/Andyhere/Z-images_models/resolve/main/SAM3.zip"
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"text_encoder": "Qwen3VL-4B-Instruct-Q4_K_M.gguf",
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"text_encoder_url": "https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct-GGUF/resolve/main/Qwen3VL-4B-Instruct-Q4_K_M.gguf",
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"text_encoder_url": "https://huggingface.co/unsloth/Qwen3-VL-8B-Instruct-GGUF/resolve/main/Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
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"text_encoder": "Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
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"text_encoder_url": "https://huggingface.co/unsloth/Qwen3-VL-8B-Instruct-GGUF/resolve/main/Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
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"text_encoder": "Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
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"text_encoder": "Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
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"text_encoder_url": "https://huggingface.co/unsloth/Qwen3-VL-8B-Instruct-GGUF/resolve/main/Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
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"text_encoder": "Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
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"text_encoder_url": "https://huggingface.co/unsloth/Qwen3-VL-8B-Instruct-GGUF/resolve/main/Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
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"text_encoder": "Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
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"text_encoder_url": "https://huggingface.co/unsloth/Qwen3-VL-8B-Instruct-GGUF/resolve/main/Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
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"text_encoder": "Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
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"text_encoder_url": "https://huggingface.co/unsloth/Qwen3-VL-8B-Instruct-GGUF/resolve/main/Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
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"vae": "ae.safetensors",
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"vae_url": "https://huggingface.co/black-forest-labs/FLUX.1-dev/resolve/main/ae.safetensors",
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"runtime_status": "recommended_safe"
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"model name": "boogu_image_turbo_hotfix_int8_convrot.safetensors",
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"text_encoder": "Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
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"text_encoder_url": "https://huggingface.co/unsloth/Qwen3-VL-8B-Instruct-GGUF/resolve/main/Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
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"vae_url": "https://huggingface.co/black-forest-labs/FLUX.1-dev/resolve/main/ae.safetensors",
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"runtime_status": "blocked_by_safe_mode",
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{
|
| 565 |
-
"model name": "boogu_image_turbo_hotfix_nvfp4.safetensors",
|
| 566 |
-
"type": "base model",
|
| 567 |
-
"base": "boogu",
|
| 568 |
-
"thumbnail": "https://huggingface.co/Comfy-Org/Boogu-Image/resolve/main/images/boogu.jpg",
|
| 569 |
-
"url": "https://huggingface.co/Comfy-Org/Boogu-Image/resolve/main/diffusion_models/boogu_image_turbo_hotfix_nvfp4.safetensors",
|
| 570 |
-
"text_encoder": "Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
|
| 571 |
-
"text_encoder_url": "https://huggingface.co/unsloth/Qwen3-VL-8B-Instruct-GGUF/resolve/main/Qwen3-VL-8B-Instruct-Q4_K_M.gguf",
|
| 572 |
-
"vae": "ae.safetensors",
|
| 573 |
-
"vae_url": "https://huggingface.co/black-forest-labs/FLUX.1-dev/resolve/main/ae.safetensors"
|
| 574 |
}
|
|
|
|
|
|
|
| 575 |
]
|
|
|
|
| 396 |
"type": "Others",
|
| 397 |
"thumbnail": "https://i.ibb.co/msQPWSQ/sam3.jpg",
|
| 398 |
"url": "https://huggingface.co/Andyhere/Z-images_models/resolve/main/SAM3.zip"
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|
| 399 |
}
|
| 400 |
+
|
| 401 |
+
|
| 402 |
]
|