Instructions to use ViTAMIn-O/ViTAMIn-O_base_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ViTAMIn-O/ViTAMIn-O_base_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ViTAMIn-O/ViTAMIn-O_base_model") 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("ViTAMIn-O/ViTAMIn-O_base_model") model = AutoModelForImageClassification.from_pretrained("ViTAMIn-O/ViTAMIn-O_base_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ba8c02e1580718924a342843c17788c4b5ccc79f6861301d579884dad4af67a
- Size of remote file:
- 787 MB
- SHA256:
- 682ee6bdf693fefcbb726a9cc5c92728874644605033e84ee7e1acdb95190d79
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