Instructions to use ProbeX/Model-J__SupViT__model_idx_0025 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_0025 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_0025") 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_0025") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0025", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ddb7363280867e7ec7c9b9125b69fac4f0812d5a2ff9a2a13422f3fbf426198d
- Size of remote file:
- 5.37 kB
- SHA256:
- 508bfd531bf59b7bc90998cb6f8eee4bc292c9ca9798477ead0b535337f2e9f4
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