Instructions to use ivensamdh/beitv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ivensamdh/beitv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ivensamdh/beitv2") 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("ivensamdh/beitv2") model = AutoModelForImageClassification.from_pretrained("ivensamdh/beitv2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae9f1b410d18a7f637b0ccc77a661d9d98cc4eb097e55beef02079c1cce69d24
- Size of remote file:
- 3.45 kB
- SHA256:
- 1fb077efc4271e6fac492f7b23f083ff5df0d6c741e7d6427c0b8524d1f7ac9a
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