Instructions to use Pamreth/vit-ena24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pamreth/vit-ena24 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Pamreth/vit-ena24") 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("Pamreth/vit-ena24") model = AutoModelForImageClassification.from_pretrained("Pamreth/vit-ena24") - Notebooks
- Google Colab
- Kaggle
| { | |
| "eval_accuracy": 0.04351145038167939, | |
| "eval_loss": 3.0898842811584473, | |
| "eval_model_preparation_time": 0.0031, | |
| "eval_runtime": 925.7714, | |
| "eval_samples_per_second": 1.415, | |
| "eval_steps_per_second": 0.177 | |
| } |