Instructions to use cvmil/vit-base-patch16-224_augmented-v2_tl 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_tl 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_tl") 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_tl") model = AutoModelForImageClassification.from_pretrained("cvmil/vit-base-patch16-224_augmented-v2_tl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from cvmil/vit-base-patch16-224_augmented-v2_tl: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/cvmil/vit-base-patch16-224_augmented-v2_tl/resolve/main/training_args.bin
- Command line
-
hf download hf://cvmil/vit-base-patch16-224_augmented-v2_tl/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/cvmil/vit-base-patch16-224_augmented-v2_tl/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 4029ab77e65cf6eddd09fcd9c14d6a8104518ad89b9def79e6deb6ef523e4b34
- Size of remote file:
- 5.5 kB
- SHA256:
- 721aa9508e9caece7c5d05f45a4198a9a5c8e8b143abaa56652a8ea17dab6adb
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