Instructions to use HorcruxNo13/mobilevitv2-1.0-imagenet1k-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HorcruxNo13/mobilevitv2-1.0-imagenet1k-256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="HorcruxNo13/mobilevitv2-1.0-imagenet1k-256") 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("HorcruxNo13/mobilevitv2-1.0-imagenet1k-256") model = AutoModelForImageClassification.from_pretrained("HorcruxNo13/mobilevitv2-1.0-imagenet1k-256") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5dc1572e8b6a9f29ab852457aec8ca1632216b3ec15b0eb06502b0ff5df09441
- Size of remote file:
- 4.09 kB
- SHA256:
- 042bca5676d3bf056732067e9377ef2cace98fc3ef8d73cdfff02cad7a7446b3
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