Instructions to use ProbeX/Model-J__SupViT__model_idx_0728 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_0728 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_0728") 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_0728") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0728", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d100c4f67f016ff81371b2474e3557e619a46eb887d02fffa52d65c81ca4009
- Size of remote file:
- 5.37 kB
- SHA256:
- ab76f40feb83314b10a06b0b8ecd8826c823d63fbf8cc9bd6753b17fdd1bf30b
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