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:
- 79a900026d60e40e7b630768f08c32d624f04e32f61fa077b007b5d72fed9067
- Size of remote file:
- 5.97 kB
- SHA256:
- bb5d91af537593cc22447d9357893700dd7aeccaed47665c842b29615610d3e6
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