Instructions to use nqvii/deit_fold_5_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nqvii/deit_fold_5_v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nqvii/deit_fold_5_v3") 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_5_v3") model = AutoModelForImageClassification.from_pretrained("nqvii/deit_fold_5_v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d380fe5e722af5aa2b99e478e5e58efdbf1adb5da617a4ff6d1d287339fab9c3
- Size of remote file:
- 5.2 kB
- SHA256:
- 5d02178f09558262f58892078ba0509159655ac37c03be97a7f54dde2d07caff
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