Instructions to use nqvii/deit_fold_2_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nqvii/deit_fold_2_v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nqvii/deit_fold_2_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_2_v3") model = AutoModelForImageClassification.from_pretrained("nqvii/deit_fold_2_v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 039b6f823c6599cb8713ffcc5e81a89455775d3ef57af00f6fc0d2a9555a8bd0
- Size of remote file:
- 5.2 kB
- SHA256:
- 9be4aec639f4cef108d46e1f4b781f2f9df97c6c81c4ed62947cb352172343a9
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