Instructions to use ProbeX/Model-J__SupViT__model_idx_0248 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_0248 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_0248") 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_0248") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0248") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9cf61f1311e00446a872a5c8d4c09a794399234598fcc7dcbbbc3537342fcc0d
- Size of remote file:
- 5.37 kB
- SHA256:
- 3b3585465d4b7edabdf2fc6b0270ae4c9469976f71960d0b7e97bf90ea98b009
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