Image-Text-to-Text
Transformers
Safetensors
English
Chinese
deepseek_vl_v2
text-generation
ocr
vision-language
deepseek
quantization
custom_code
8-bit precision
custom
Instructions to use SamMikaelson/deepseek-ocr-int8-uniform with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamMikaelson/deepseek-ocr-int8-uniform with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="SamMikaelson/deepseek-ocr-int8-uniform", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("SamMikaelson/deepseek-ocr-int8-uniform", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use SamMikaelson/deepseek-ocr-int8-uniform with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SamMikaelson/deepseek-ocr-int8-uniform" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SamMikaelson/deepseek-ocr-int8-uniform", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SamMikaelson/deepseek-ocr-int8-uniform
- SGLang
How to use SamMikaelson/deepseek-ocr-int8-uniform 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 "SamMikaelson/deepseek-ocr-int8-uniform" \ --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": "SamMikaelson/deepseek-ocr-int8-uniform", "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 "SamMikaelson/deepseek-ocr-int8-uniform" \ --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": "SamMikaelson/deepseek-ocr-int8-uniform", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SamMikaelson/deepseek-ocr-int8-uniform with Docker Model Runner:
docker model run hf.co/SamMikaelson/deepseek-ocr-int8-uniform
Download quantization_config.json from SamMikaelson/deepseek-ocr-int8-uniform: direct link, hf CLI and curl.
- Browser
- Download file 496 kB
-
https://huggingface.co/SamMikaelson/deepseek-ocr-int8-uniform/resolve/main/quantization_config.json
- Command line
-
hf download hf://SamMikaelson/deepseek-ocr-int8-uniform/quantization_config.json
-
curl -L -o quantization_config.json https://huggingface.co/SamMikaelson/deepseek-ocr-int8-uniform/resolve/main/quantization_config.json
496 kB
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