Instructions to use ProbeX/Model-J__SupViT__model_idx_0904 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_0904 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_0904") 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_0904") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0904") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 186a8fd6424c912afeb1d295b9799ed8830d578db94556501985b5aecc8cd628
- Size of remote file:
- 5.37 kB
- SHA256:
- fd97bc2b2fae1ccc96acfcf6acc68228dd2c26a34a6a96bf104e067e851227a3
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