Instructions to use microsoft/cvt-13-384-22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/cvt-13-384-22k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/cvt-13-384-22k") 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-13-384-22k") model = AutoModelForImageClassification.from_pretrained("microsoft/cvt-13-384-22k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/cvt-13-384-22k: direct link, hf CLI and curl.
- Browser
- Download file 80.3 MB
-
https://huggingface.co/microsoft/cvt-13-384-22k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://microsoft/cvt-13-384-22k/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/cvt-13-384-22k/resolve/main/pytorch_model.bin
80.3 MB
- Xet hash:
- bf6240d7fd874ee31ea1462365e85eeaab09008c9328c36439fe396a01fb260d
- Size of remote file:
- 80.3 MB
- SHA256:
- 5217b8419800e0799c328b75a22a9ac593af28541caa7408b9751e5218dcb6d9
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