Tuana/qwen35-08b-text2sql

qwen35-08b-text2sql

Tuana/qwen35-08b-text2sql is a demo Text-to-SQL model fine-tuned from `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. 1.Generate a synthetic SQL instruction dataset
2. 2.Fine-tune a small Qwen base model on Vertex AI
3. 3.Merge the LoRA adapter into the base checkpoint
4. 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

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: