Instructions to use tedad09/donut-test-tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tedad09/donut-test-tmp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="tedad09/donut-test-tmp")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("tedad09/donut-test-tmp") model = AutoModelForImageTextToText.from_pretrained("tedad09/donut-test-tmp") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use tedad09/donut-test-tmp with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tedad09/donut-test-tmp" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tedad09/donut-test-tmp", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/tedad09/donut-test-tmp
- SGLang
How to use tedad09/donut-test-tmp 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 "tedad09/donut-test-tmp" \ --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": "tedad09/donut-test-tmp", "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 "tedad09/donut-test-tmp" \ --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": "tedad09/donut-test-tmp", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use tedad09/donut-test-tmp with Docker Model Runner:
docker model run hf.co/tedad09/donut-test-tmp
Donut-Epochs3-Data0
Browse files- preprocessor_config.json +4 -4
- special_tokens_map.json +2 -14
- tokenizer.json +0 -0
preprocessor_config.json
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"processor_class": "DonutProcessor",
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size":
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}
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"processor_class": "DonutProcessor",
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": {
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special_tokens_map.json
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"bos_token": {
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"content": "<s>",
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"bos_token": {
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"content": "<s>",
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tokenizer.json
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