Instructions to use HorcruxNo13/vit-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HorcruxNo13/vit-base-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="HorcruxNo13/vit-base-patch16-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("HorcruxNo13/vit-base-patch16-224") model = AutoModelForImageClassification.from_pretrained("HorcruxNo13/vit-base-patch16-224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 15.0, | |
| "total_flos": 1.16237984421888e+18, | |
| "train_loss": 0.475440772374471, | |
| "train_runtime": 1200.7807, | |
| "train_samples_per_second": 12.492, | |
| "train_steps_per_second": 0.05 | |
| } |