Instructions to use ahmedesmail16/Project_Class_6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmedesmail16/Project_Class_6B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ahmedesmail16/Project_Class_6B") 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_6B") model = AutoModelForImageClassification.from_pretrained("ahmedesmail16/Project_Class_6B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4a700b76debe33357f8ef9ae936a8d5831ef84ccc1aab48a0d5b39a8528b020
- Size of remote file:
- 343 MB
- SHA256:
- 7606739223ccdd346311713576f32809664f4c12e4af039964ff70c97b194b41
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