Instructions to use SpacemiT/PaddleOCR-VL0.9B 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/PaddleOCR-VL0.9B 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/PaddleOCR-VL0.9B # Run inference directly in the terminal: llama cli -hf SpacemiT/PaddleOCR-VL0.9B
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf SpacemiT/PaddleOCR-VL0.9B # Run inference directly in the terminal: llama cli -hf SpacemiT/PaddleOCR-VL0.9B
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/PaddleOCR-VL0.9B # Run inference directly in the terminal: ./llama-cli -hf SpacemiT/PaddleOCR-VL0.9B
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/PaddleOCR-VL0.9B # Run inference directly in the terminal: ./build/bin/llama-cli -hf SpacemiT/PaddleOCR-VL0.9B
Use Docker
docker model run hf.co/SpacemiT/PaddleOCR-VL0.9B
- LM Studio
- Jan
- vLLM
How to use SpacemiT/PaddleOCR-VL0.9B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SpacemiT/PaddleOCR-VL0.9B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SpacemiT/PaddleOCR-VL0.9B", "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/SpacemiT/PaddleOCR-VL0.9B
- Ollama
How to use SpacemiT/PaddleOCR-VL0.9B with Ollama:
ollama run hf.co/SpacemiT/PaddleOCR-VL0.9B
- Unsloth Studio
How to use SpacemiT/PaddleOCR-VL0.9B 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 SpacemiT/PaddleOCR-VL0.9B 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 SpacemiT/PaddleOCR-VL0.9B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for SpacemiT/PaddleOCR-VL0.9B to start chatting
- Docker Model Runner
How to use SpacemiT/PaddleOCR-VL0.9B with Docker Model Runner:
docker model run hf.co/SpacemiT/PaddleOCR-VL0.9B
- Lemonade
How to use SpacemiT/PaddleOCR-VL0.9B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull SpacemiT/PaddleOCR-VL0.9B
Run and chat with the model
lemonade run user.PaddleOCR-VL0.9B-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
- Xet hash:
- 09235544ccfd85ab2e98684cbfadfacb2b50f4113680f1b36201c7eccf4ed792
- Size of remote file:
- 1.85 GB
- SHA256:
- 23d91d1a438d792394a35c57252ab8f1eca62f11ef4b5909642102c02d6fcf64
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