Instructions to use WaveMatrix/PaddleOCR-VL-1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WaveMatrix/PaddleOCR-VL-1.5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="WaveMatrix/PaddleOCR-VL-1.5")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WaveMatrix/PaddleOCR-VL-1.5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use WaveMatrix/PaddleOCR-VL-1.5 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "WaveMatrix/PaddleOCR-VL-1.5" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "WaveMatrix/PaddleOCR-VL-1.5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/WaveMatrix/PaddleOCR-VL-1.5
- SGLang
How to use WaveMatrix/PaddleOCR-VL-1.5 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "WaveMatrix/PaddleOCR-VL-1.5" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "WaveMatrix/PaddleOCR-VL-1.5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "WaveMatrix/PaddleOCR-VL-1.5" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "WaveMatrix/PaddleOCR-VL-1.5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use WaveMatrix/PaddleOCR-VL-1.5 with Docker Model Runner:
docker model run hf.co/WaveMatrix/PaddleOCR-VL-1.5
Download python/model.embed_tokens.weight.npy from WaveMatrix/PaddleOCR-VL-1.5: direct link, hf CLI and curl.
- Browser
- Download file 424 MB
-
https://huggingface.co/WaveMatrix/PaddleOCR-VL-1.5/resolve/main/python/model.embed_tokens.weight.npy
- Command line
-
hf download hf://WaveMatrix/PaddleOCR-VL-1.5/python/model.embed_tokens.weight.npy
-
curl -L -o model.embed_tokens.weight.npy https://huggingface.co/WaveMatrix/PaddleOCR-VL-1.5/resolve/main/python/model.embed_tokens.weight.npy
424 MB
- Xet hash:
- ceadcc892628c38c72b3cfb6fc2f82aacfd3083ff35ab9f620993f442d111961
- Size of remote file:
- 424 MB
- SHA256:
- bbb214e22f31d0b4b7e1646b6f5551cd80f2eea99db91feabc668052d4aee71c
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