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:
- e76a1ad05a7e5d27f059197133a64e20adcaeb3a11f80b10deca34f9b2c3378e
- Size of remote file:
- 1.47 kB
- SHA256:
- deb8689fba982b5a238419469a8505baefa68a7eef41e05e707edd4bff5625a7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.