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:
- 33935204d308ab51c066550a60174bd05c6153c33f33aa5ff51f0f790a5ac17f
- Size of remote file:
- 80.7 MB
- SHA256:
- d782bacd92bd57ab1b7e59e5cbff7f1a102e094cc338ac72186af080ebd5abc1
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