Instructions to use ProbeX/Model-J__SupViT__model_idx_0680 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_0680 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_0680") 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_0680") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0680", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d0aae81a5d7f885121f0d64b4c061261f89b69d107297546eae7446788d27f1
- Size of remote file:
- 5.37 kB
- SHA256:
- 490008ce7d25f0101f7cd499caa91adb2484c23f05765f7fb5c3ad1b52a5f313
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