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/paddleocr_vl_1-5_tokenizer/tokenizer.json from WaveMatrix/PaddleOCR-VL-1.5: direct link, hf CLI and curl.
- Browser
- Download file 11.2 MB
-
https://huggingface.co/WaveMatrix/PaddleOCR-VL-1.5/resolve/main/python/paddleocr_vl_1-5_tokenizer/tokenizer.json
- Command line
-
hf download hf://WaveMatrix/PaddleOCR-VL-1.5/python/paddleocr_vl_1-5_tokenizer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/WaveMatrix/PaddleOCR-VL-1.5/resolve/main/python/paddleocr_vl_1-5_tokenizer/tokenizer.json
11.2 MB
- Xet hash:
- 0671503fc5d01f50c20977ea2a430ecc5916a84d955e4f2b83b065a9125e9232
- Size of remote file:
- 11.2 MB
- SHA256:
- c8a215a59183d0d0781adc33bacd3ce6162716f7fd568fb30234a74d69803a7d
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