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lmstudio-community
/
Qwen2-VL-72B-Instruct-GGUF

Image-Text-to-Text
GGUF
English
multimodal
conversational
Model card Files Files and versions
xet
Community
1

Instructions to use lmstudio-community/Qwen2-VL-72B-Instruct-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 lmstudio-community/Qwen2-VL-72B-Instruct-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 lmstudio-community/Qwen2-VL-72B-Instruct-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf lmstudio-community/Qwen2-VL-72B-Instruct-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 lmstudio-community/Qwen2-VL-72B-Instruct-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf lmstudio-community/Qwen2-VL-72B-Instruct-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 lmstudio-community/Qwen2-VL-72B-Instruct-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    ./llama-cli -hf lmstudio-community/Qwen2-VL-72B-Instruct-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 lmstudio-community/Qwen2-VL-72B-Instruct-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf lmstudio-community/Qwen2-VL-72B-Instruct-GGUF:Q4_K_M
    Use Docker
    docker model run hf.co/lmstudio-community/Qwen2-VL-72B-Instruct-GGUF:Q4_K_M
  • LM Studio
  • Jan
  • vLLM

    How to use lmstudio-community/Qwen2-VL-72B-Instruct-GGUF with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "lmstudio-community/Qwen2-VL-72B-Instruct-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": "lmstudio-community/Qwen2-VL-72B-Instruct-GGUF",
    		"messages": [
    			{
    				"role": "user",
    				"content": [
    					{
    						"type": "text",
    						"text": "Describe this image in one sentence."
    					},
    					{
    						"type": "image_url",
    						"image_url": {
    							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
    						}
    					}
    				]
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/lmstudio-community/Qwen2-VL-72B-Instruct-GGUF:Q4_K_M
  • Ollama

    How to use lmstudio-community/Qwen2-VL-72B-Instruct-GGUF with Ollama:

    ollama run hf.co/lmstudio-community/Qwen2-VL-72B-Instruct-GGUF:Q4_K_M
  • Unsloth Desktop
  • Docker Model Runner

    How to use lmstudio-community/Qwen2-VL-72B-Instruct-GGUF with Docker Model Runner:

    docker model run hf.co/lmstudio-community/Qwen2-VL-72B-Instruct-GGUF:Q4_K_M
  • Lemonade

    How to use lmstudio-community/Qwen2-VL-72B-Instruct-GGUF with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull lmstudio-community/Qwen2-VL-72B-Instruct-GGUF:Q4_K_M
    Run and chat with the model
    lemonade run user.Qwen2-VL-72B-Instruct-GGUF-Q4_K_M
    List all available models
    lemonade list
  • Atomic Chat
Qwen2-VL-72B-Instruct-GGUF
231 GB
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  • 1 contributor
History: 9 commits
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bartowski
Update README.md
fcfdda0 verified over 1 year ago
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