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 model.safetensors from al-css/PagesClassificationModel: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/al-css/PagesClassificationModel/resolve/main/model.safetensors
- Command line
-
hf download hf://al-css/PagesClassificationModel/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/al-css/PagesClassificationModel/resolve/main/model.safetensors
343 MB
- Xet hash:
- fab70c6104063bebc46b3cc113fcd80821666978ef2bc79e6fcb070a9bd86466
- Size of remote file:
- 343 MB
- SHA256:
- 9948abd4a253ae611307d0bfbcdc8214b740aedc28afa744dc11d271d2e21e1b
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