Instructions to use ProbeX/Model-J__SupViT__model_idx_0323 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_0323 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_0323") 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_0323") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0323") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f075b9acaa0bb96775fa9757fc7bfaa47cf642510886ba7db70ef2e24e4906d
- Size of remote file:
- 5.37 kB
- SHA256:
- 93b3e3d82809a47dcab5f9fb0367b926baaabdcb88806f99603159d3016ca497
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