Instructions to use roschmid/dog-races with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roschmid/dog-races with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="roschmid/dog-races") 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("roschmid/dog-races") model = AutoModelForImageClassification.from_pretrained("roschmid/dog-races") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5bb357c185641d1dc2f8e11c6492b16d96cc86bb8bd4e9c686718d8b77f2a382
- Size of remote file:
- 343 MB
- SHA256:
- 8d8d851e33b9ceff84c108db4aadc3c214e68d96582b28441aff70c322aaf7da
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