Instructions to use molsen/beit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use molsen/beit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="molsen/beit") 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("molsen/beit") model = AutoModelForImageClassification.from_pretrained("molsen/beit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5078cbb61da3f9b5e86da49a21763dfaa5d46fe80597ccad60471dca2d0df110
- Size of remote file:
- 3.45 kB
- SHA256:
- 975faae5cc144be388f50bc9a62dccb90c4d586a2818a72fe7c71d4640d9f695
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