Instructions to use ogimgio/vit-base-highways-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ogimgio/vit-base-highways-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ogimgio/vit-base-highways-2") 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("ogimgio/vit-base-highways-2") model = AutoModelForImageClassification.from_pretrained("ogimgio/vit-base-highways-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 10.0, | |
| "eval_accuracy": 0.7, | |
| "eval_loss": 1.2668935060501099, | |
| "eval_runtime": 0.3131, | |
| "eval_samples_per_second": 31.941, | |
| "eval_steps_per_second": 6.388, | |
| "total_flos": 1.4800970016387072e+17, | |
| "train_loss": 0.10321386102586985, | |
| "train_runtime": 163.7528, | |
| "train_samples_per_second": 11.664, | |
| "train_steps_per_second": 1.466 | |
| } |