Instructions to use ProbeX/Model-J__SupViT__model_idx_0565 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_0565 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_0565") 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_0565") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0565", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 014b50437f7ce9cca3d0c65f278341fbfc6e36294c37ccbb7de70c53bd0d23f8
- Size of remote file:
- 5.37 kB
- SHA256:
- 4e2631087ae1c35a0c11c78c8689e12a63b0f7639d4c4cbe6bf36cafd3ec2466
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