Instructions to use gerbejon/webpage_labeling_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gerbejon/webpage_labeling_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gerbejon/webpage_labeling_classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("gerbejon/webpage_labeling_classifier") model = AutoModelForImageClassification.from_pretrained("gerbejon/webpage_labeling_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gerbejon/webpage_labeling_classifier: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/gerbejon/webpage_labeling_classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://gerbejon/webpage_labeling_classifier/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/gerbejon/webpage_labeling_classifier/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- bcde01c6c5fdde561f2d33bfb973a64f0e68bc3b32a986c3db7323268ae981a8
- Size of remote file:
- 5.18 kB
- SHA256:
- 65282ddf11ab6e4ec65dda75f680032a37bec36a5a848fe77dcf8a2613b6629d
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