Instructions to use hkivancoral/smids_10x_beit_large_adamax_001_fold1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hkivancoral/smids_10x_beit_large_adamax_001_fold1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hkivancoral/smids_10x_beit_large_adamax_001_fold1") 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("hkivancoral/smids_10x_beit_large_adamax_001_fold1") model = AutoModelForImageClassification.from_pretrained("hkivancoral/smids_10x_beit_large_adamax_001_fold1") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened about 1 year ago
by
SFconvertbot