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:
- deb1121d98458c2047cb99aa7815e162806c4ef42532fc630d9f37da00ecd58a
- Size of remote file:
- 343 MB
- SHA256:
- 183298473c54c273fe768ed0b696455dfd3e71448662f597c7602e1be1fe46a8
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