Instructions to use emre570/google-vit-large-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emre570/google-vit-large-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="emre570/google-vit-large-finetuned") 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("emre570/google-vit-large-finetuned") model = AutoModelForImageClassification.from_pretrained("emre570/google-vit-large-finetuned") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3db6533a38f14f3d0a426321a8d7332ca32e80c152b968775a386b31ebbdc4b5
- Size of remote file:
- 2.43 GB
- SHA256:
- 823ac7b2a83e6142bbf00c0667d6cf819b1ae0aeb302ada9c6b8430abc3c6591
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