Instructions to use mobilint/Qwen2-VL-2B-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 mobilint/Qwen2-VL-2B-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 mobilint/Qwen2-VL-2B-Instruct-GGUF # Run inference directly in the terminal: llama cli -hf mobilint/Qwen2-VL-2B-Instruct-GGUF
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf mobilint/Qwen2-VL-2B-Instruct-GGUF # Run inference directly in the terminal: llama cli -hf mobilint/Qwen2-VL-2B-Instruct-GGUF
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 mobilint/Qwen2-VL-2B-Instruct-GGUF # Run inference directly in the terminal: ./llama-cli -hf mobilint/Qwen2-VL-2B-Instruct-GGUF
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 mobilint/Qwen2-VL-2B-Instruct-GGUF # Run inference directly in the terminal: ./build/bin/llama-cli -hf mobilint/Qwen2-VL-2B-Instruct-GGUF
Use Docker
docker model run hf.co/mobilint/Qwen2-VL-2B-Instruct-GGUF
- LM Studio
- Jan
- Ollama
How to use mobilint/Qwen2-VL-2B-Instruct-GGUF with Ollama:
ollama run hf.co/mobilint/Qwen2-VL-2B-Instruct-GGUF
- Unsloth Desktop
- Docker Model Runner
How to use mobilint/Qwen2-VL-2B-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/mobilint/Qwen2-VL-2B-Instruct-GGUF
- Lemonade
How to use mobilint/Qwen2-VL-2B-Instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mobilint/Qwen2-VL-2B-Instruct-GGUF
Run and chat with the model
lemonade run user.Qwen2-VL-2B-Instruct-GGUF-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Upload preprocessor_config.json with huggingface_hub
Browse files- preprocessor_config.json +22 -0
preprocessor_config.json
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{
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"auto_map": {
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"AutoProcessor": "proxy_qwen2_vl.MobilintQwen2VLProcessor"
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},
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"min_pixels": 3136,
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"max_pixels": 12845056,
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"patch_size": 14,
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"temporal_patch_size": 2,
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"merge_size": 2,
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"image_mean": [
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0.48145466,
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0.4578275,
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0.40821073
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],
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"image_std": [
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0.26862954,
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0.26130258,
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0.27577711
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],
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"image_processor_type": "Qwen2VLImageProcessorFast",
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"processor_class": "MobilintQwen2VLProcessor"
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}
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