Instructions to use jonglet/mbvit_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonglet/mbvit_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jonglet/mbvit_small") 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("jonglet/mbvit_small") model = AutoModelForImageClassification.from_pretrained("jonglet/mbvit_small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94c588a62675d457c517ce8710709d0b3090b554829ca20814a74d5ba28b8ae6
- Size of remote file:
- 20 MB
- SHA256:
- 6a9b2192021dd944cb49c07b4a51aed136e35da24814ec8c52d6036e5c8e380c
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