Instructions to use ProbeX/Model-J__SupViT__model_idx_0701 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_0701 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_0701") 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_0701") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0701") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2678eb492ee3c07770908ece539e95e6e80bda37e854bc4aa0b4974987c0d3e
- Size of remote file:
- 5.37 kB
- SHA256:
- f7fd527155e62c726487ef27187a4e857e7a8b206dd45d432449bf2e053c230c
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