Instructions to use ProbeX/Model-J__SupViT__model_idx_0279 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_0279 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_0279") 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_0279") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0279", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0e70baf15bca7ed82188efb029034c6da50c9066c04eb6888e15c240ceddd773
- Size of remote file:
- 5.37 kB
- SHA256:
- 2a4841f5d6fc8254cdd29b4eab817cb735c13c5dc9bca32be73d9f542680cca6
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