Instructions to use ProbeX/Model-J__SupViT__model_idx_0562 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_0562 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_0562") 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_0562") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0562") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c03d5ee00a47490abcbe47ad5f6298b54bab2cc6aeecfdeb80296b1e7a58fc36
- Size of remote file:
- 5.37 kB
- SHA256:
- e7afa1f040521b0b2657a4bdce957d3fa6125744c0badf8631b2277e83b3094a
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