Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Augusto777/vit-base-patch16-224-RU5-10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Augusto777/vit-base-patch16-224-RU5-10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Augusto777/vit-base-patch16-224-RU5-10") 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("Augusto777/vit-base-patch16-224-RU5-10") model = AutoModelForImageClassification.from_pretrained("Augusto777/vit-base-patch16-224-RU5-10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Augusto777/vit-base-patch16-224-RU5-10: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/Augusto777/vit-base-patch16-224-RU5-10/resolve/main/training_args.bin
- Command line
-
hf download hf://Augusto777/vit-base-patch16-224-RU5-10/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Augusto777/vit-base-patch16-224-RU5-10/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 7e97c0c2443415f8c8ed4b7c0a9334129f049116c0c30781911707a41c98a7ba
- Size of remote file:
- 4.73 kB
- SHA256:
- 7affcc2311e3dbc4344be7301793729ad828934f1c6f2e3c4dc3e70c419a7f1d
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