Instructions to use HPAI-BSC/SuSy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPAI-BSC/SuSy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="HPAI-BSC/SuSy") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("HPAI-BSC/SuSy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 99a8a8d3d1bd197744c123249c7a077ce66d1015549d8971cc873efbbe6eefa0
- Size of remote file:
- 50.8 MB
- SHA256:
- fa10fae300ee2742c7a373b6c3332c2595b461954b8f5616d2d382ef2751020e
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