Instructions to use SivilTaram/poet-sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SivilTaram/poet-sql with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SivilTaram/poet-sql")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SivilTaram/poet-sql") model = AutoModel.from_pretrained("SivilTaram/poet-sql") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c51b888ab33abd0e911033c9110b579eead1033e759720c62551131958f11ff
- Size of remote file:
- 1.63 GB
- SHA256:
- 016682931be4be7850541b0fe47d7176c10c100db1d7dbf56d6d411f138c14e3
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