Instructions to use ProbeX/Model-J__SupViT__model_idx_0421 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_0421 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_0421", 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_0421") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0421", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f270948faeecf696c9dc31c4f6fd857fbd0ef156b0a5735b7044647b794caa19
- Size of remote file:
- 343 MB
- SHA256:
- 48f1547b26a7aa1f642606afe8c49fe58f79ce4308e83481402490ed9f544f20
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