Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Augusto777/vit-base-patch16-224-RU2-40 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Augusto777/vit-base-patch16-224-RU2-40 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Augusto777/vit-base-patch16-224-RU2-40") 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-RU2-40") model = AutoModelForImageClassification.from_pretrained("Augusto777/vit-base-patch16-224-RU2-40", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Augusto777/vit-base-patch16-224-RU2-40: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/Augusto777/vit-base-patch16-224-RU2-40/resolve/main/training_args.bin
- Command line
-
hf download hf://Augusto777/vit-base-patch16-224-RU2-40/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Augusto777/vit-base-patch16-224-RU2-40/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- c03443da7ae3e8c3c88e41e08f5c36225430822f39dfb7044fa92d496d8fd3b3
- Size of remote file:
- 4.73 kB
- SHA256:
- 1e9bb4624396e01e91d65ca370e2271a9bd810ac3ff9bbc51bcfc7f8bdb076d5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.