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
Commit ·
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Parent(s): a03a517
add config
Browse files- config.json +1 -1
config.json
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{
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"architectures": [
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"attention_probs_dropout_prob": 0.0,
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"drop_path_rate": 0.1,
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{
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"architectures": [
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"BeitForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"drop_path_rate": 0.1,
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