Instructions to use ProbeX/Model-J__SupViT__model_idx_0808 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_0808 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_0808") 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_0808") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0808", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ff76be6169426e72f0eddc5fc2484dc65c3ad5ddf693b0e74efd76037c12c03
- Size of remote file:
- 5.37 kB
- SHA256:
- aec58a89d61a1a58c35378e9aa4933e77b530a12f679fef04e4afba9d44f08be
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