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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15f7333394eafa95020006fdda233f0a542c0cda2b1fd562cc6beee97640a83f
- Size of remote file:
- 80.3 MB
- SHA256:
- 77c0a16fa66a3c762159966806b8b22e13c4f0e6c879544e83621e6053f5a8e2
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