Instructions to use microsoft/beit-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/beit-base-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/beit-base-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-base-patch16-224") model = AutoModelForImageClassification.from_pretrained("microsoft/beit-base-patch16-224") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c5ad2d7a1be1c9b39f0c17c3cfc92ad979934045045c492f3304a60e6c04335
- Size of remote file:
- 350 MB
- SHA256:
- 5574866866a425d7fc2b21e400f064d67d3650529ef9b9ab6b1ff3f9b6c9cbb6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.