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:
- e8da41e0ba404d71e0ed8e9a1e2f38105bca970a1b3a8ef0ef20c79c860671b9
- Size of remote file:
- 3.9 kB
- SHA256:
- 85dc6e031901c7afef521e8b117cdd95478d1789234aab79e3a3c364f0de0f90
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