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unsloth
/
GLM-4.6-GGUF

Text Generation
Transformers
GGUF
English
Chinese
unsloth
imatrix
conversational
Model card Files Files and versions
xet
Community
13

Instructions to use unsloth/GLM-4.6-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use unsloth/GLM-4.6-GGUF with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="unsloth/GLM-4.6-GGUF")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("unsloth/GLM-4.6-GGUF", dtype="auto")
  • llama-cpp-python

    How to use unsloth/GLM-4.6-GGUF with llama-cpp-python:

    # !pip install llama-cpp-python
    
    from llama_cpp import Llama
    
    llm = Llama.from_pretrained(
    	repo_id="unsloth/GLM-4.6-GGUF",
    	filename="BF16/GLM-4.6-BF16-00001-of-00015.gguf",
    )
    
    llm.create_chat_completion(
    	messages = [
    		{
    			"role": "user",
    			"content": "What is the capital of France?"
    		}
    	]
    )
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use unsloth/GLM-4.6-GGUF with llama.cpp:

    Install from brew
    brew install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
    # Run inference directly in the terminal:
    llama-cli -hf unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
    # Run inference directly in the terminal:
    llama-cli -hf unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
    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 unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
    # Run inference directly in the terminal:
    ./llama-cli -hf unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
    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 unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
    Use Docker
    docker model run hf.co/unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
  • LM Studio
  • Jan
  • vLLM

    How to use unsloth/GLM-4.6-GGUF with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "unsloth/GLM-4.6-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": "unsloth/GLM-4.6-GGUF",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
  • SGLang

    How to use unsloth/GLM-4.6-GGUF with SGLang:

    Install from pip and serve model
    # Install SGLang from pip:
    pip install sglang
    # Start the SGLang server:
    python3 -m sglang.launch_server \
        --model-path "unsloth/GLM-4.6-GGUF" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "unsloth/GLM-4.6-GGUF",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker images
    docker run --gpus all \
        --shm-size 32g \
        -p 30000:30000 \
        -v ~/.cache/huggingface:/root/.cache/huggingface \
        --env "HF_TOKEN=<secret>" \
        --ipc=host \
        lmsysorg/sglang:latest \
        python3 -m sglang.launch_server \
            --model-path "unsloth/GLM-4.6-GGUF" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "unsloth/GLM-4.6-GGUF",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Ollama

    How to use unsloth/GLM-4.6-GGUF with Ollama:

    ollama run hf.co/unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
  • Unsloth Studio

    How to use unsloth/GLM-4.6-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 unsloth/GLM-4.6-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 unsloth/GLM-4.6-GGUF to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for unsloth/GLM-4.6-GGUF to start chatting
  • Pi

    How to use unsloth/GLM-4.6-GGUF with Pi:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama-server -hf unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
    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": "unsloth/GLM-4.6-GGUF:UD-Q4_K_XL"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Hermes Agent new

    How to use unsloth/GLM-4.6-GGUF with Hermes Agent:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama-server -hf unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
    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 unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
    Run Hermes
    hermes
  • Docker Model Runner

    How to use unsloth/GLM-4.6-GGUF with Docker Model Runner:

    docker model run hf.co/unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
  • Lemonade

    How to use unsloth/GLM-4.6-GGUF with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull unsloth/GLM-4.6-GGUF:UD-Q4_K_XL
    Run and chat with the model
    lemonade run user.GLM-4.6-GGUF-UD-Q4_K_XL
    List all available models
    lemonade list
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

GLM 4.5, 4.6, 4.7 Quality of Life updates

pinned
#13 opened 5 months ago by
danielhanchen

Multiple chat template fixes

pinned
πŸš€β€οΈ 7
14
#2 opened 8 months ago by
danielhanchen

I see GGUFs for this model were just re-uploaded - what's changed?

❀️ 1
5
#12 opened 5 months ago by
Mdubbya

Perplexity?

#10 opened 7 months ago by
dxkna

Llama.cpp reasoning_content

3
#8 opened 8 months ago by
brianw

Missing tensor 'blk.92.nextn.embed_tokens.weight error

πŸ‘ 3
5
#7 opened 8 months ago by
MadManDan

what's the best Q4 quant?

4
#4 opened 8 months ago by
SlavikF

Is it the same architecture than GLM 4.5 ?

πŸ‘βž• 2
5
#3 opened 8 months ago by
AliceThirty

Fingers crossed for the 4.6-air

βž•β€οΈ 6
14
#1 opened 8 months ago by
aaron-newsome
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