Instructions to use microsoft/cvt-13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/cvt-13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/cvt-13") 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("microsoft/cvt-13") model = AutoModelForImageClassification.from_pretrained("microsoft/cvt-13", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f796d889909db4967ea08f58550c6ab9f53b19ae4c33699379b467ebd6656da
- Size of remote file:
- 80.2 MB
- SHA256:
- 71576c56ac8aaabc1db4e74d86d0316ba1fe7ecff397bbe81b33cf874df8eee2
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