Instructions to use ProbeX/Model-J__SupViT__model_idx_0264 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_0264 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_0264") 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_0264") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0264", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58ae1d37b827fc8fd9a0048e23472137a481b6e260dd67ce42b89e5e9530575f
- Size of remote file:
- 5.37 kB
- SHA256:
- 27a6e6db77932570026d14d0908237a7e69090a351609f18ba0364130114eb9c
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