Instructions to use ProbeX/Model-J__SupViT__model_idx_0351 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_0351 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_0351") 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_0351") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0351") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5bc90337d53c2530bb7961157d0f342aa76cd1cc70b88ea57b847075448a14e5
- Size of remote file:
- 5.37 kB
- SHA256:
- d285a486106d066a47f16485d90ed52d702e40f439526d0b05cf1a72eaac8a8f
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