Instructions to use cvmil/vit-base-patch16-224_augmented-v2_fft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cvmil/vit-base-patch16-224_augmented-v2_fft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="cvmil/vit-base-patch16-224_augmented-v2_fft") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("cvmil/vit-base-patch16-224_augmented-v2_fft") model = AutoModelForImageClassification.from_pretrained("cvmil/vit-base-patch16-224_augmented-v2_fft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
Verified signatured95f566 -
Model save
Verified signature0fe7225 -
Model save
Verified signature91836be -
Training in progress, epoch 19
Verified signature4fd4998 -
Model save
Verified signature28595f4 -
Model save
Verified signature7959889 -
Model save
Verified signature6b4e51a -
initial commit
Verified signature56c07d7