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
Download production.zip from Nekshay/Finetuned-MobilVIT: direct link, hf CLI and curl.
- Browser
- Download file 46.2 kB
-
https://huggingface.co/Nekshay/Finetuned-MobilVIT/resolve/main/production.zip
- Command line
-
hf download hf://Nekshay/Finetuned-MobilVIT/production.zip
-
curl -L -o production.zip https://huggingface.co/Nekshay/Finetuned-MobilVIT/resolve/main/production.zip
46.2 kB
- Xet hash:
- afb8dbe259b61c628115f28ec49506427743dfbc7397753d4d2bb39115f3d5d0
- Size of remote file:
- 46.2 kB
- SHA256:
- 8803fb661ae1a6609660fdec8c242d98b7c34ca87baf9c18215adb44f8ca5930
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