Instructions to use AmitMidday/Dogs-Breed-Classification-Using-Vision-Transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AmitMidday/Dogs-Breed-Classification-Using-Vision-Transformers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="AmitMidday/Dogs-Breed-Classification-Using-Vision-Transformers") 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("AmitMidday/Dogs-Breed-Classification-Using-Vision-Transformers") model = AutoModelForImageClassification.from_pretrained("AmitMidday/Dogs-Breed-Classification-Using-Vision-Transformers", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c79fa2db0475395d00dacbd070b13d8438c6f0056b4ae3ad133740a0a2899e6e
- Size of remote file:
- 627 Bytes
- SHA256:
- 9fe20bb773222c07b057b09c06618d60d4316c6cd20bd5076e13c003aa425020
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