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")# pip install -U transformers accelerate # 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/chat_template.jinja from WaveMatrix/PaddleOCR-VL-1.5: direct link, hf CLI and curl.
- Browser
- Download file 1.47 kB
-
https://huggingface.co/WaveMatrix/PaddleOCR-VL-1.5/resolve/main/python/paddleocr_vl_1-5_tokenizer/chat_template.jinja
- Command line
-
hf download hf://WaveMatrix/PaddleOCR-VL-1.5/python/paddleocr_vl_1-5_tokenizer/chat_template.jinja
-
curl -L -o chat_template.jinja https://huggingface.co/WaveMatrix/PaddleOCR-VL-1.5/resolve/main/python/paddleocr_vl_1-5_tokenizer/chat_template.jinja
1.47 kB
| {%- if not add_generation_prompt is defined -%} | |
| {%- set add_generation_prompt = true -%} | |
| {%- endif -%} | |
| {%- if not cls_token is defined -%} | |
| {%- set cls_token = "<|begin_of_sentence|>" -%} | |
| {%- endif -%} | |
| {%- if not eos_token is defined -%} | |
| {%- set eos_token = "</s>" -%} | |
| {%- endif -%} | |
| {{- cls_token -}} | |
| {%- for message in messages -%} | |
| {%- if message["role"] == "user" -%} | |
| {{- "User: " -}} | |
| {%- for content in message["content"] -%} | |
| {%- if content["type"] == "image" -%} | |
| {{ "<|IMAGE_START|><|IMAGE_PLACEHOLDER|><|IMAGE_END|>" }} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {%- for content in message["content"] -%} | |
| {%- if content["type"] == "text" -%} | |
| {{ content["text"] }} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {{ "\n" -}} | |
| {%- elif message["role"] == "assistant" -%} | |
| {{- "Assistant:\n" -}} | |
| {%- for content in message["content"] -%} | |
| {%- if content["type"] == "text" -%} | |
| {{ content["text"] }} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {{ eos_token -}} | |
| {%- elif message["role"] == "system" -%} | |
| {%- for content in message["content"] -%} | |
| {%- if content["type"] == "text" -%} | |
| {{ content["text"] + "\n" }} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {%- if add_generation_prompt -%} | |
| {{- "Assistant:\n" -}} | |
| {%- endif -%} | |