Instructions to use ProbeX/Model-J__SupViT__model_idx_0136 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_0136 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_0136") 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_0136") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0136", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cfc66d7d707b7392a23d71f81113e7255ece7917eecafc809ca867b8a4a5cd86
- Size of remote file:
- 5.37 kB
- SHA256:
- 31013b2553923a86d5c106ba8b8135e860eeedf7cb67a1fb1c308681acc42081
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