Instructions to use ProbeX/Model-J__SupViT__model_idx_0667 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_0667 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_0667") 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_0667") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0667") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ad9634ee4f9b494039f2d6ba0b8326fa580ce1640c93f9c6ccadbc2ac60d7c2
- Size of remote file:
- 5.37 kB
- SHA256:
- 1a77f91fb56374b144df9592c985f2f34f269d0cc55b3bae70f0816bbee9f214
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