Instructions to use nqvii/deit_fold_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nqvii/deit_fold_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nqvii/deit_fold_1") 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("nqvii/deit_fold_1") model = AutoModelForImageClassification.from_pretrained("nqvii/deit_fold_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f9425dd958bc3fbb37d7017c2ac6ddd4d3c4673d107d4e877076cf01b440656
- Size of remote file:
- 5.2 kB
- SHA256:
- 482cd2ecf2cb5334703865e9d7e720cecfb1c0f131d6140a558e1ff71d93139d
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