Instructions to use SiddharthaM/beit-base-patch16-224-pt22k-ft22k-rim_one-new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SiddharthaM/beit-base-patch16-224-pt22k-ft22k-rim_one-new with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SiddharthaM/beit-base-patch16-224-pt22k-ft22k-rim_one-new") 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("SiddharthaM/beit-base-patch16-224-pt22k-ft22k-rim_one-new") model = AutoModelForImageClassification.from_pretrained("SiddharthaM/beit-base-patch16-224-pt22k-ft22k-rim_one-new", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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