Instructions to use TheSleepyJo/mobilevitv2_fold_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheSleepyJo/mobilevitv2_fold_5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TheSleepyJo/mobilevitv2_fold_5") 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("TheSleepyJo/mobilevitv2_fold_5") model = AutoModelForImageClassification.from_pretrained("TheSleepyJo/mobilevitv2_fold_5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97131e2d151c2b3c1981f08b0091b6daf0d6c89b73c18d803b6fea1fcd406e29
- Size of remote file:
- 17.7 MB
- SHA256:
- 99d7cee783d032166f683bdd81a29d66aecca5b7c9c312441c8edbf243fe5b4c
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