Instructions to use microsoft/beit-large-patch16-224-pt22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/beit-large-patch16-224-pt22k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/beit-large-patch16-224-pt22k") 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, BeitForMaskedImageModeling processor = AutoImageProcessor.from_pretrained("microsoft/beit-large-patch16-224-pt22k") model = BeitForMaskedImageModeling.from_pretrained("microsoft/beit-large-patch16-224-pt22k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (456eb0e35fb2c9bbafb62c904a4f0ef1ea2cfbcc) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>c3c80a4
-
Add vision tag
d1b5d42
-
add model
0d9ece4 -
add config
6579c95 -
Update .gitattributes
7c7cdd5
-
Update preprocessor_config.json
a96fd0e
-
Fix typo
34c7e0a -
Fix typo
9d0ce28 -
Add model card
526f02c -
Add model card
9d9dbd9
-
First commit
209e227 -
initial commit
9bd7f13