Instructions to use theoberva/UBCO-Model-512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use theoberva/UBCO-Model-512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="theoberva/UBCO-Model-512") 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("theoberva/UBCO-Model-512") model = AutoModelForImageClassification.from_pretrained("theoberva/UBCO-Model-512") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa15d7340e50fba26b87373a658e35d93249c20f80413c7c111df4327809bdba
- Size of remote file:
- 4.09 kB
- SHA256:
- 100fc04cd6b0254f3c8ae5ef075b799d61b302fb97cc84f5caaba91e0bd26a19
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