Instructions to use caffeic/text-to-sql-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use caffeic/text-to-sql-model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("caffeic/text-to-sql-model", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40c033ac21ea00298399d4557a260ceb6a62fec762d4615dc918c72f08c7d9ca
- Size of remote file:
- 1.38 kB
- SHA256:
- 265edfb643a2133b26cbbb62f724b80dc636b6504f99fee38ea7c51aee480d8c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.