Instructions to use nqvii/deit_fold_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nqvii/deit_fold_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nqvii/deit_fold_2") 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") model = AutoModelForImageClassification.from_pretrained("nqvii/deit_fold_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc91505205f8e0e3b693a7557077266b35fdb0f75c592d5a790e73b6057bed5c
- Size of remote file:
- 5.2 kB
- SHA256:
- 1d0899b3aee820d6303be470092cfe58359a146b9fb2ef92ca79dca091fa2c2a
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