Instructions to use tiamda/gemma-text-to-sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiamda/gemma-text-to-sql with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tiamda/gemma-text-to-sql", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tiamda/gemma-text-to-sql: direct link, hf CLI and curl.
- Browser
- Download file 5.62 kB
-
https://huggingface.co/tiamda/gemma-text-to-sql/resolve/main/training_args.bin
- Command line
-
hf download hf://tiamda/gemma-text-to-sql/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tiamda/gemma-text-to-sql/resolve/main/training_args.bin
5.62 kB
- Xet hash:
- 345c4a0ba5cce07838bdd2a3bfc11520bcb4bd363e66811b8f84db177ee6e93b
- Size of remote file:
- 5.62 kB
- SHA256:
- 89d4e7e7a407f53d5858a96689d146d39b5aafcb6b4679d31f9d8cd7673693ce
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