Instructions to use ahmedesmail16/Project_Class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmedesmail16/Project_Class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ahmedesmail16/Project_Class") 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("ahmedesmail16/Project_Class") model = AutoModelForImageClassification.from_pretrained("ahmedesmail16/Project_Class") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9dcc09a77960238713093d686011b1931df95f40d6c568d4db8eb10b68aea112
- Size of remote file:
- 343 MB
- SHA256:
- 4b91f477c909ff8ca1f36fa9276fec30e2e0530bcdeaad961534c8baf4ac9a3d
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