Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Augusto777/vit-base-patch16-224-RX1-24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Augusto777/vit-base-patch16-224-RX1-24 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Augusto777/vit-base-patch16-224-RX1-24") 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-RX1-24") model = AutoModelForImageClassification.from_pretrained("Augusto777/vit-base-patch16-224-RX1-24", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 209 Bytes
6687328 | 1 2 3 4 5 6 7 8 | {
"epoch": 22.4,
"eval_accuracy": 0.8431372549019608,
"eval_loss": 0.5686964988708496,
"eval_runtime": 1.0601,
"eval_samples_per_second": 48.108,
"eval_steps_per_second": 1.887
} |