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:
- 942effdaa007936dc456312548472dc08c1ab0c5551ce12d09925b106da52701
- Size of remote file:
- 343 MB
- SHA256:
- 8328385ee4cbcf6a80d5428d8339dfa1f6b6f8faedf6c37908ab03dc75f52063
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