Image-Text-to-Text
Transformers
Safetensors
multilingual
deepseekocr
feature-extraction
deepseek
vision-language
ocr
custom_code
Instructions to use specsGuy/Deepseek-ocr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use specsGuy/Deepseek-ocr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="specsGuy/Deepseek-ocr", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("specsGuy/Deepseek-ocr", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use specsGuy/Deepseek-ocr with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "specsGuy/Deepseek-ocr" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "specsGuy/Deepseek-ocr", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/specsGuy/Deepseek-ocr
- SGLang
How to use specsGuy/Deepseek-ocr 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 "specsGuy/Deepseek-ocr" \ --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": "specsGuy/Deepseek-ocr", "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 "specsGuy/Deepseek-ocr" \ --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": "specsGuy/Deepseek-ocr", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use specsGuy/Deepseek-ocr with Docker Model Runner:
docker model run hf.co/specsGuy/Deepseek-ocr
| from transformers import AutoTokenizer | |
| class DeepseekOCRTokenizer: | |
| """ | |
| This is a thin wrapper for using an existing tokenizer (e.g., DeepSeek or GPT2) | |
| under the custom model_type 'deepseekocr'. | |
| """ | |
| def from_pretrained(cls, *args, **kwargs): | |
| # You can swap this base model if your tokenizer came from another checkpoint | |
| return AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder", *args, **kwargs) | |