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
Download pytorch_model.bin from microsoft/cvt-13-384: direct link, hf CLI and curl.
- Browser
- Download file 80.3 MB
-
https://huggingface.co/microsoft/cvt-13-384/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://microsoft/cvt-13-384@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/cvt-13-384/resolve/refs%2Fpr%2F2/pytorch_model.bin
80.3 MB
- Xet hash:
- 9f9208b04a9c646bcb7b38723cb653389285fab872d8e1de5ba42c12412b722e
- Size of remote file:
- 80.3 MB
- SHA256:
- bac7a58899c41b4cd90bfded50f1d4e1cf283c2d3255e3fce7ff7350e0d23438
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