Instructions to use sngsfydy/MobileViT_with_Trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sngsfydy/MobileViT_with_Trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sngsfydy/MobileViT_with_Trainer") 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("sngsfydy/MobileViT_with_Trainer") model = AutoModelForImageClassification.from_pretrained("sngsfydy/MobileViT_with_Trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f674a42f23b279e404379fb16e534073d18340b47da72f7ab8fcc0c8fecd84f7
- Size of remote file:
- 19.9 MB
- SHA256:
- f0051c5626ef9d236bf1fcb94461187f72579f2345c6888f33007e2db14b7d1b
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