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license: apache-2.0
base_model: Qwen/Qwen3.5-0.8B
library_name: transformers
pipeline_tag: text-generation
tags:
- text-to-sql
- sql
- qwen
- demo
- vertex-ai
- synthetic-data
---
# qwen35-08b-text2sql
`Tuana/qwen35-08b-text2sql` is a **demo Text-to-SQL model** fine-tuned from [`Qwen/Qwen3.5-0.8B`](https://huggingface.co/Qwen/Qwen3.5-0.8B).
It was fine-tuned on a small, specific synthetic SQL dataset for demonstration purposes. It is not intended to be a general Text-to-SQL model for arbitrary schemas or production databases.
## Model Details
- **Base model:** `Qwen/Qwen3.5-0.8B`
- **Task demo:** Text-to-SQL style SQL generation
- **Fine-tuning method:** LoRA SFT, merged into a full checkpoint
- **Training platform:** Google Cloud Vertex AI
- **Training container:** Hugging Face PyTorch Training Deep Learning Container
- **Dataset:** `Tuana/synthetic-sql-dataset`
- **Model format:** Merged `transformers` checkpoint
## What This Model Demonstrates
This model demonstrates a small fine-tuning workflow:
1. Generate a synthetic SQL instruction dataset
2. Fine-tune a small Qwen base model on Vertex AI
3. Merge the LoRA adapter into the base checkpoint
4. Serve or compare the result in a small demo app
The demo dataset uses a small synthetic database domain with tables such as:
- `department`
- `management`
- `head`
The model should be viewed as a demo artifact for this specific setup, not as a robust SQL assistant.
## Example Prompt Format
```text
Given this database schema:
CREATE TABLE department (
department_id VARCHAR,
name VARCHAR,
creation VARCHAR
);
CREATE TABLE management (
department_id VARCHAR,
head_id VARCHAR,
temporary_acting VARCHAR
);
CREATE TABLE head (
head_id VARCHAR,
name VARCHAR,
born_state VARCHAR
);
Write a SQL query for:
List all department names.
SQL:
``` |