Instructions to use ProbeX/Model-J__SupViT__model_idx_0657 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_0657 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_0657") 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_0657") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0657") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3793a71484ea3202163ea4c9ff04161ff6c29fc5436783e63dd0e8dc307e3f3a
- Size of remote file:
- 5.37 kB
- SHA256:
- 5332553fcf765410a4460229b3900b293014f3b27bf1ec912509b8109e02654e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.