Instructions to use ghermoso/vit-eGTZANplus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghermoso/vit-eGTZANplus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ghermoso/vit-eGTZANplus") 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("ghermoso/vit-eGTZANplus") model = AutoModelForImageClassification.from_pretrained("ghermoso/vit-eGTZANplus") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- baa59bc42af2b86bd37fc989c9bced2537522be310c6cc5e4a7f0df628cead4d
- Size of remote file:
- 4.47 kB
- SHA256:
- c839c24594cae9354c376c7d15c2fb9af9b0d9474867636a45fe7b1f4acb33ee
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