Instructions to use ahmedesmail16/Project_Class_Aug_Model_beit-base-patch16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmedesmail16/Project_Class_Aug_Model_beit-base-patch16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ahmedesmail16/Project_Class_Aug_Model_beit-base-patch16") 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_Aug_Model_beit-base-patch16") model = AutoModelForImageClassification.from_pretrained("ahmedesmail16/Project_Class_Aug_Model_beit-base-patch16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2dfb636106f523423d82d19bc7a1093f334c77eb1bc1729f9165ff066ad69808
- Size of remote file:
- 343 MB
- SHA256:
- 75e3c65f6670e9e9c4dff41b88822a44213a629d4d9022d552587e7391712ab1
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