Instructions to use ProbeX/Model-J__SupViT__model_idx_0762 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_0762 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_0762") 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_0762") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0762") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 447c7b367a660f8befd57db752d6036c4c8a1c052b25cbafdb8845fc9bde250c
- Size of remote file:
- 5.37 kB
- SHA256:
- e5d2b253427374047d48ff5e03161ac2860a2e5c01c541ff227a8a820dfcd168
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