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
- Xet hash:
- 7ca437f76d65f8f968a96aa46e7a0518d2f8b8269910bbbcdb217af67b7e2885
- Size of remote file:
- 933 MB
- SHA256:
- eba7737c7311a2dde461833139dd51f64cee27d050de3420dfe8fe140a017bcf
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