Instructions to use ProbeX/Model-J__SupViT__model_idx_0254 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_0254 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_0254", device_map="auto") 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_0254") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0254", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ef58ad9457d0b44e7727de79bbc89ca296e19ecba2e8f062d7604dc80d104af
- Size of remote file:
- 5.37 kB
- SHA256:
- e6d6c59dcb6d87d770f24a6d6c995ea2e76e094cf91a70e096762576d846ad16
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