Instructions to use microsoft/beit-base-patch16-224-pt22k-ft22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/beit-base-patch16-224-pt22k-ft22k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/beit-base-patch16-224-pt22k-ft22k") 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/beit-base-patch16-224-pt22k-ft22k") model = AutoModelForImageClassification.from_pretrained("microsoft/beit-base-patch16-224-pt22k-ft22k", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download config.json from microsoft/beit-base-patch16-224-pt22k-ft22k: direct link, hf CLI and curl.
- Browser
- Download file 1.67 MB
-
https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k/resolve/refs%2Fpr%2F4/config.json
- Command line
-
hf download hf://microsoft/beit-base-patch16-224-pt22k-ft22k@refs/pr/4/config.json
-
curl -L -o config.json https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k/resolve/refs%2Fpr%2F4/config.json
1.67 MB
File too large to display, you can check the raw version instead.