Instructions to use microsoft/beit-large-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/beit-large-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/beit-large-patch16-224") 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/beit-large-patch16-224") model = AutoModelForImageClassification.from_pretrained("microsoft/beit-large-patch16-224") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 712aefb2d82548263aa9572c77fe4baebb1a13b4e9a126d222e3ebf6264e6f0b
- Size of remote file:
- 1.23 GB
- SHA256:
- d92061f7389194d1bc7e332e6b7e8312970240209ea5c6ff37862171cbda2f19
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.