Instructions to use ProbeX/Model-J__SupViT__model_idx_0121 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_0121 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_0121") 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_0121") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0121") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ba6b7ed0bc91139e91afaa4d6688f15b0781bf0d03f7a6fb03b335f973a3f21
- Size of remote file:
- 343 MB
- SHA256:
- 79d4d351edc1ad0cfbbf078e2730ac3759280bcaaddbdcf10ae7b3851f6a173d
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