Instructions to use jaypratap/vit-mae-base-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jaypratap/vit-mae-base-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jaypratap/vit-mae-base-classifier") 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("jaypratap/vit-mae-base-classifier") model = AutoModelForImageClassification.from_pretrained("jaypratap/vit-mae-base-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a93e52fafa233d2a852d5b9d94851c08847db91c645b0bd637bb686b8b593c87
- Size of remote file:
- 4.98 kB
- SHA256:
- 188c8de82d65a6531d870a4dc0eb41588a0cdf4f1b672f3d7a457e6227c6b347
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