Instructions to use ProbeX/Model-J__SupViT__model_idx_0297 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_0297 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_0297") 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_0297") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0297") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 311620d40baa1a5dc6678cbd9c26b773f5a3b5b7156c7897b87dbf6966f33531
- Size of remote file:
- 343 MB
- SHA256:
- 457855269ae51373fb3a4f005baa9541bdb02bddc49f8b1640b4d26b4252dd9c
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