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:
- 26554ff679ccdb7e1d748820f950f8b855a639eff9bfde35521f22f150d8120e
- Size of remote file:
- 175 MB
- SHA256:
- d6618202d7719b1f373ca375e7dd25beb5e107dfd5951e1ec93cd050daead4b6
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