Instructions to use rawhad/fb-nougat-small-split with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rawhad/fb-nougat-small-split with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="rawhad/fb-nougat-small-split")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("rawhad/fb-nougat-small-split") model = AutoModelForMultimodalLM.from_pretrained("rawhad/fb-nougat-small-split", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use rawhad/fb-nougat-small-split with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rawhad/fb-nougat-small-split" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rawhad/fb-nougat-small-split", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/rawhad/fb-nougat-small-split
- SGLang
How to use rawhad/fb-nougat-small-split 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 "rawhad/fb-nougat-small-split" \ --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": "rawhad/fb-nougat-small-split", "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 "rawhad/fb-nougat-small-split" \ --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": "rawhad/fb-nougat-small-split", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use rawhad/fb-nougat-small-split with Docker Model Runner:
docker model run hf.co/rawhad/fb-nougat-small-split
- Xet hash:
- b270d1bff4944e31195c7e3cd71bd1e1b909d550fd4e3deb5123ab58167b27f1
- Size of remote file:
- 693 MB
- SHA256:
- f9f01c089dc36ce01b4e3a4a0a9b937ca3d8cc45a838cdea08e3bc0ffe30de37
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