Instructions to use OmAlve/reading-steiner-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OmAlve/reading-steiner-v2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OmAlve/reading-steiner-v2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8fd5ab8466da56173631b3573df50cd43e2d6dd2257874a01488cf3feff42307
- Size of remote file:
- 12.8 MB
- SHA256:
- 2596c00b2926c443462a981dad6731b648ae9458720a4280fd66e33090073e15
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