| --- |
| base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct |
| tags: |
| - text-to-sql |
| - qlora |
| - fine-tuned |
| --- |
| |
| # NL2SQL — Qwen2.5-Coder-1.5B fine-tuned for text-to-SQL |
|
|
| QLoRA fine-tuned version of Qwen2.5-Coder-1.5B-Instruct, trained on a custom |
| e-commerce schema to translate natural language questions into SQL queries. |
|
|
| - **Base model**: Qwen/Qwen2.5-Coder-1.5B-Instruct |
| - **Method**: QLoRA (4-bit), LoRA r=8, alpha=16 |
| - **Training data**: ~270 examples (40 hand-written + 230 Groq-generated, |
| manually reviewed), grounded in a 6-table e-commerce schema |
| - **Eval**: execution accuracy against a live SQLite DB (see repo README) |
|
|
| ## Usage |
|
|
| Prompt format: |
| \`\`\` |
| You are a SQL expert. Given a database schema and a question, write the SQL query that answers it. |
|
|
| ### Schema: |
| {schema} |
|
|
| ### Question: |
| {question} |
|
|
| ### SQL: |
| \`\`\` |
|
|
| Full training code, dataset generation, and evaluation script: [github link] |
