Instructions to use nqvii/deit_fold_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nqvii/deit_fold_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nqvii/deit_fold_3") 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_3") model = AutoModelForImageClassification.from_pretrained("nqvii/deit_fold_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac4013e05e92a641a7badfe7ce00a93cd0b3adecd7467112d024ee318775c058
- Size of remote file:
- 5.2 kB
- SHA256:
- e1d95c4d93e9fefc9af2e79bf086b5bf57100dd5f758d264f7cb57c3bc3b64ae
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