Instructions to use bryanzhou008/vit-base-patch16-224-in21k-finetuned-inaturalist with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bryanzhou008/vit-base-patch16-224-in21k-finetuned-inaturalist with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bryanzhou008/vit-base-patch16-224-in21k-finetuned-inaturalist") 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("bryanzhou008/vit-base-patch16-224-in21k-finetuned-inaturalist") model = AutoModelForImageClassification.from_pretrained("bryanzhou008/vit-base-patch16-224-in21k-finetuned-inaturalist", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 80.0, | |
| "eval_accuracy": 0.8638888888888889, | |
| "eval_loss": 1.2210274934768677, | |
| "eval_runtime": 3.1179, | |
| "eval_samples_per_second": 230.927, | |
| "eval_steps_per_second": 1.924 | |
| } |