README.md

# Finetuning LLaMa + Text-to-SQL 

This walkthrough shows you how to fine-tune LLaMa-7B on a Text-to-SQL dataset, and then use it for inference against
any database of structured data using LlamaIndex.


This code is taken and adapted from the Modal `doppel-bot` repo: https://github.com/modal-labs/doppel-bot.

### Stack

- LlamaIndex
- Modal
- Hugging Face datasets
- OpenLLaMa 
- Peft


### Steps for running

Please see the notebook (TODO) for full instructions.

In the meantime you can run each step individually as below:

Loading data:
`modal run src.load_data_sql`

Finetuning:
`modal run --detach src.finetune_sql`

Inference:
`modal run src.inference_sql_llamaindex::main --query "Which city has the highest population?" --sqlite-file-path "nbs/cities.db"`

(Optional) Downloading model weights:
`modal run src.download_weights --output-dir out_model`