Instructions to use SpacemiT/FastVLM-0.5B 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 SpacemiT/FastVLM-0.5B 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 SpacemiT/FastVLM-0.5B:Q4_1 # Run inference directly in the terminal: llama cli -hf SpacemiT/FastVLM-0.5B:Q4_1
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf SpacemiT/FastVLM-0.5B:Q4_1 # Run inference directly in the terminal: llama cli -hf SpacemiT/FastVLM-0.5B:Q4_1
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 SpacemiT/FastVLM-0.5B:Q4_1 # Run inference directly in the terminal: ./llama-cli -hf SpacemiT/FastVLM-0.5B:Q4_1
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 SpacemiT/FastVLM-0.5B:Q4_1 # Run inference directly in the terminal: ./build/bin/llama-cli -hf SpacemiT/FastVLM-0.5B:Q4_1
Use Docker
docker model run hf.co/SpacemiT/FastVLM-0.5B:Q4_1
- LM Studio
- Jan
- Ollama
How to use SpacemiT/FastVLM-0.5B with Ollama:
ollama run hf.co/SpacemiT/FastVLM-0.5B:Q4_1
- Unsloth Desktop
- Docker Model Runner
How to use SpacemiT/FastVLM-0.5B with Docker Model Runner:
docker model run hf.co/SpacemiT/FastVLM-0.5B:Q4_1
- Lemonade
How to use SpacemiT/FastVLM-0.5B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull SpacemiT/FastVLM-0.5B:Q4_1
Run and chat with the model
lemonade run user.FastVLM-0.5B-Q4_1
List all available models
lemonade list
- Atomic Chat
upload configs/K1/config.json
Browse files- configs/K1/config.json +18 -0
configs/K1/config.json
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{
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"architectures": [
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"LlavaQwen2ForCausalLM"
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],
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"vision_model": {
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"model_path": "../../fastvlm_vision.f16.onnx",
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"input_size": 512,
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"ep_config": {
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"SPACEMIT_EP_INTRA_THREAD_NUM": "4",
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"SPACEMIT_EP_INTER_THREAD_NUM": "1",
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"SPACEMIT_EP_INTRA_THREAD_AFFINITY": "0;1;2;3"
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}
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},
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"text_model": {
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"model_path": "../../fastvlm-text-0.5B-Q4_1.gguf",
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"hidden_size": 896
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}
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}
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