Instructions to use dima806/67_cat_breeds_image_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/67_cat_breeds_image_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dima806/67_cat_breeds_image_detection") 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("dima806/67_cat_breeds_image_detection") model = AutoModelForImageClassification.from_pretrained("dima806/67_cat_breeds_image_detection") - Notebooks
- Google Colab
- Kaggle
See https://www.kaggle.com/code/dima806/67-cat-breed-image-detection-vit for more details.
- Downloads last month
- 260
Model tree for dima806/67_cat_breeds_image_detection
Base model
google/vit-base-patch16-224-in21k