Instructions to use ProbeX/Model-J__SupViT__model_idx_0621 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_0621 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_0621") 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_0621") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0621", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de9f51e4e4926d41fa9e93d395f0fd4581947ddbf21dca038ad799e287dd6549
- Size of remote file:
- 5.37 kB
- SHA256:
- f3c0271f284d7704f3c79d09ad6273a93c3d6e44455907fa9f010c1b21008b07
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