Instructions to use microsoft/cvt-13-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/cvt-13-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/cvt-13-384") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("microsoft/cvt-13-384") model = AutoModelForImageClassification.from_pretrained("microsoft/cvt-13-384", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add TF weights (#1)
- Add TF weights (89b91d2dc942403103d2ae0f5f0bc1f9f0dc730e) Co-authored-by: Mathieu Jouffroy <CCMat@users.noreply.huggingface.co>a143314
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Update preprocessor_config.json
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Update README.md
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Update
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initial commit
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