Instructions to use ProbeX/Model-J__SupViT__model_idx_0465 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_0465 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_0465") 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_0465") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0465") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a56bae82b67a8ee66e4721741eaf5daa5d60d61598c14a50252a71d041372a05
- Size of remote file:
- 5.37 kB
- SHA256:
- 06f67888b76bbd4a9e4e36d68421455c7e509aa034f5426f033ee2a063e7092f
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