Instructions to use nqvii/deit_fold_4_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nqvii/deit_fold_4_v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nqvii/deit_fold_4_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_4_v3") model = AutoModelForImageClassification.from_pretrained("nqvii/deit_fold_4_v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c825d804db5df4362b5791204488baf33607d47569c54dda506deeb0134bd3d
- Size of remote file:
- 5.2 kB
- SHA256:
- 45134de7f879fd811ce4e83c3b95dba38370fc0515c81686f766f09655028941
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