Instructions to use ProbeX/Model-J__SupViT__model_idx_0948 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_0948 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_0948", device_map="auto") 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_0948") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0948", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e5ede309159cf6d388ebeaf4565b81d783c0b41f0f06cb3f804ced77b4e9cdb
- Size of remote file:
- 5.37 kB
- SHA256:
- 1c56a43036b0c9c9aa3fc87eb33f2acead7befd79e0843e397f800e1dd31439e
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