Instructions to use saracandu/stldec_formulae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saracandu/stldec_formulae with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="saracandu/stldec_formulae", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("saracandu/stldec_formulae", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9eea0cb28694c30758a99f13f0aa9554d481aff52ece647f48df3880632e5ca9
- Size of remote file:
- 806 MB
- SHA256:
- 6b69e8f1f53917174671d3db2685734441f1a68843ac09874544b2bcb278f771
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