Instructions to use achyudev/vit-base-patch16-224-in21k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use achyudev/vit-base-patch16-224-in21k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="achyudev/vit-base-patch16-224-in21k") 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("achyudev/vit-base-patch16-224-in21k") model = AutoModelForImageClassification.from_pretrained("achyudev/vit-base-patch16-224-in21k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
achyuth commited on
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Parent(s): 99992b7
Training in progress, epoch 10
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pytorch_model.bin
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