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:
- aa6d7bb1d2204e0119e4bbc491255c7144fffa009e5ee825fe9d1d63b021aa82
- Size of remote file:
- 17.7 MB
- SHA256:
- c86c4a959364848e9e5138c70cdb029ec514976f8f490ae3915914bf5af56225
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