Instructions to use cvmil/vit-hybrid-base-bit-384_augmented-v2_fft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cvmil/vit-hybrid-base-bit-384_augmented-v2_fft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="cvmil/vit-hybrid-base-bit-384_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 AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("cvmil/vit-hybrid-base-bit-384_augmented-v2_fft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from cvmil/vit-hybrid-base-bit-384_augmented-v2_fft: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/cvmil/vit-hybrid-base-bit-384_augmented-v2_fft/resolve/main/training_args.bin
- Command line
-
hf download hf://cvmil/vit-hybrid-base-bit-384_augmented-v2_fft/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/cvmil/vit-hybrid-base-bit-384_augmented-v2_fft/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 02f734b25b8cf41d4f7e78229cf2213266968332c0219979952bf92befab1160
- Size of remote file:
- 5.5 kB
- SHA256:
- 898aeccb0d38471b1a731579973aea23d1fd62f9b4fb54ec211a51f0f2065957
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