Instructions to use sylvain471/beit_doc_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sylvain471/beit_doc_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sylvain471/beit_doc_classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("sylvain471/beit_doc_classification") model = AutoModelForImageClassification.from_pretrained("sylvain471/beit_doc_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sylvain471/beit_doc_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/sylvain471/beit_doc_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://sylvain471/beit_doc_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sylvain471/beit_doc_classification/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- e81f4cc783c5f0e62b531d17f2c5f94c053adaf507b13aa611703487e4f76f35
- Size of remote file:
- 4.03 kB
- SHA256:
- 631ee13b1e3bdaa49056a14c291287ffe97a6a46ff5b14386113f7f57f4a67e7
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