Instructions to use ProbeX/Model-J__SupViT__model_idx_0374 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__SupViT__model_idx_0374 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__SupViT__model_idx_0374") 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("ProbeX/Model-J__SupViT__model_idx_0374") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0374") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8bd7e69da2ffa684aae42a98d108a27120d1da3ada3ea1aac8ae6249ec6b3e24
- Size of remote file:
- 5.37 kB
- SHA256:
- cfc43c81f6eb9fc515562fc487702ac42edbe057ad8affac753d11a555ad632c
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