Instructions to use ProbeX/Model-J__SupViT__model_idx_0769 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_0769 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_0769") 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_0769") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0769", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17f0c0b76c3c1977553ccddbea53da74131a12e9a12b87d7977621cadb0eb0b9
- Size of remote file:
- 5.37 kB
- SHA256:
- e351d36b51f5d31ba83bb829dd5d07f7f0f02851640283735eb4b7ddff84447e
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