Instructions to use Nekshay/Finetuned-MobilVIT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nekshay/Finetuned-MobilVIT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Nekshay/Finetuned-MobilVIT") 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("Nekshay/Finetuned-MobilVIT") model = AutoModelForImageClassification.from_pretrained("Nekshay/Finetuned-MobilVIT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3b6392f596d28989acfba4f61054ee9b69367d0f61e772acc4c047f244228d9
- Size of remote file:
- 13.6 kB
- SHA256:
- 5a563e754c4a08a116ea1c0a663db945ff0381c055548e26c7a20c63b889fff1
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