Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Augusto777/vit-base-patch16-224-R1-40 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Augusto777/vit-base-patch16-224-R1-40 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Augusto777/vit-base-patch16-224-R1-40") 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-R1-40") model = AutoModelForImageClassification.from_pretrained("Augusto777/vit-base-patch16-224-R1-40", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 210 Bytes
8766c8b | 1 2 3 4 5 6 7 8 | {
"epoch": 39.74,
"eval_accuracy": 0.7540983606557377,
"eval_loss": 1.7211973667144775,
"eval_runtime": 1.2098,
"eval_samples_per_second": 50.423,
"eval_steps_per_second": 1.653
} |