Instructions to use ProbeX/Model-J__SupViT__model_idx_0421 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_0421 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_0421") 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_0421") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0421", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3e48a1ac24dfc62d39d3599159ed4332f2e2519ec7812b6a9b88b172a74f29a
- Size of remote file:
- 5.37 kB
- SHA256:
- a41edb031c7fbb722969a41b763490216abb27aa1f05a6f4a1d92581c42cf081
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