Instructions to use al-css/PagesClassificationModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use al-css/PagesClassificationModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="al-css/PagesClassificationModel") 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("al-css/PagesClassificationModel") model = AutoModelForImageClassification.from_pretrained("al-css/PagesClassificationModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from al-css/PagesClassificationModel: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/al-css/PagesClassificationModel/resolve/0df9680c9c46122b884534caeaaadbe81312e39d/training_args.bin
- Command line
-
hf download hf://al-css/PagesClassificationModel@0df9680c9c46122b884534caeaaadbe81312e39d/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/al-css/PagesClassificationModel/resolve/0df9680c9c46122b884534caeaaadbe81312e39d/training_args.bin
5.18 kB
- Xet hash:
- fbd04651aa8e99d1d69d738cc98a382339ee06f4343fc679f3d602c14c2beda6
- Size of remote file:
- 5.18 kB
- SHA256:
- b0908b181b47e12bb7f29b272c40dcf4ef22e7cec74933821cee82e450d2eff2
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