Instructions to use Prakit/donut_ie_cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prakit/donut_ie_cls with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Prakit/donut_ie_cls")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("Prakit/donut_ie_cls") model = AutoModelForImageTextToText.from_pretrained("Prakit/donut_ie_cls") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Prakit/donut_ie_cls with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Prakit/donut_ie_cls" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Prakit/donut_ie_cls", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Prakit/donut_ie_cls
- SGLang
How to use Prakit/donut_ie_cls 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 "Prakit/donut_ie_cls" \ --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": "Prakit/donut_ie_cls", "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 "Prakit/donut_ie_cls" \ --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": "Prakit/donut_ie_cls", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Prakit/donut_ie_cls with Docker Model Runner:
docker model run hf.co/Prakit/donut_ie_cls
- Xet hash:
- e9898ff4faf5ba0b524f1c1d8fed5b11ae56157f52ef10d7908a00ab3f5b0000
- Size of remote file:
- 809 MB
- SHA256:
- 08bc38c294e8ab437f876ecebdb3b0cd45bf2b85b01a233eb4e4ed82d5e2cc5c
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