Instructions to use Sena/dog with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sena/dog with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sena/dog") 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("Sena/dog") model = AutoModelForImageClassification.from_pretrained("Sena/dog") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4cc7031d24aece12c46ad101117deeb5a07e50448095c0b32686fe717558a58d
- Size of remote file:
- 343 MB
- SHA256:
- 2d8263ccc66a35d121a731b29c8af6a35a1c6b6f32d255c1f4ace92c5e751635
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