Instructions to use satendrakumar/gemma-text-to-sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use satendrakumar/gemma-text-to-sql with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("satendrakumar/gemma-text-to-sql", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from satendrakumar/gemma-text-to-sql: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/satendrakumar/gemma-text-to-sql/resolve/main/training_args.bin
- Command line
-
hf download hf://satendrakumar/gemma-text-to-sql/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/satendrakumar/gemma-text-to-sql/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- 6650d60ee8000c51e180f501ef7c3a3b8c50ea9559335a2f0f6e407c964efe74
- Size of remote file:
- 5.78 kB
- SHA256:
- 14dfdaf0112fd61514420c2046ba7860a2fff18e9d5822cce3c2fec4596db76c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.