Instructions to use HorcruxNo13/beit-base-patch16-224-pt22k-ft22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HorcruxNo13/beit-base-patch16-224-pt22k-ft22k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="HorcruxNo13/beit-base-patch16-224-pt22k-ft22k") 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/beit-base-patch16-224-pt22k-ft22k") model = AutoModelForImageClassification.from_pretrained("HorcruxNo13/beit-base-patch16-224-pt22k-ft22k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 3.0, | |
| "total_flos": 2.77880533604352e+17, | |
| "train_loss": 3.9848953088124595, | |
| "train_runtime": 321.3932, | |
| "train_samples_per_second": 9.334, | |
| "train_steps_per_second": 0.075 | |
| } |