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

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

PaddleOCR-VL0.9B / configs /K3 /config.json

alex-spacemit

Upload PaddleOCR-VL0.9B package files

6e25e8d verified 1 day ago

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	{
	"architectures": ["PaddleOCR"],
	"vision_model": {"model_path": "../../paddleocr_vision.float.onnx", "input_size": 784, "input_width": 784, "input_height": 784, "ep_config": {"SPACEMIT_EP_INTRA_THREAD_NUM": "8", "SPACEMIT_EP_INTER_THREAD_NUM": "1", "SPACEMIT_EP_INTRA_THREAD_AFFINITY": "8;9;10;11;12;13;14;15"}},
	"text_model": {"model_path": "../../paddleocr-vl-text-q41.gguf", "hidden_size": 1024},
	"vision_preprocess": {"type": "normalize", "rescale_factor": 0.00392156862745098, "image_mean": [0.5, 0.5, 0.5], "image_std": [0.5, 0.5, 0.5], "layout": "NCHW"}
	}