Instructions to use ahishamm/vit-large-augmented-ph2-patch-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahishamm/vit-large-augmented-ph2-patch-32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ahishamm/vit-large-augmented-ph2-patch-32") 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("ahishamm/vit-large-augmented-ph2-patch-32") model = AutoModelForImageClassification.from_pretrained("ahishamm/vit-large-augmented-ph2-patch-32") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 4.0, | |
| "total_flos": 2.42817580228608e+18, | |
| "train_loss": 0.02911639397127041, | |
| "train_runtime": 866.2055, | |
| "train_samples_per_second": 10.159, | |
| "train_steps_per_second": 0.637 | |
| } |