Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Augusto777/vit-base-patch16-224-R1-10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Augusto777/vit-base-patch16-224-R1-10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Augusto777/vit-base-patch16-224-R1-10") 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-R1-10") model = AutoModelForImageClassification.from_pretrained("Augusto777/vit-base-patch16-224-R1-10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Augusto777/vit-base-patch16-224-R1-10: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/Augusto777/vit-base-patch16-224-R1-10/resolve/main/training_args.bin
- Command line
-
hf download hf://Augusto777/vit-base-patch16-224-R1-10/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Augusto777/vit-base-patch16-224-R1-10/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- c0b18ada7b9d700136eee8dccf9a04b0bd479fb5c0e0e907d22ac414c7dd9619
- Size of remote file:
- 4.73 kB
- SHA256:
- 71a53c03c24ea3e3fe241b06a61a2fe56214427ecd99a5dd60035456d37b762b
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