README.md

---
base_model: onekq-ai/OneSQL-v0.1-Qwen-32B
tags:
- text-generation-inference
- transformers
- qwen2
- gguf
license: apache-2.0
language:
- en
---

# Introduction

This model is the GGUF version of [OneSQL-v0.1-Qwen-32B](https://huggingface.co/onekq-ai/OneSQL-v0.1-Qwen-32B). You can also find it on [Ollama](https://ollama.com/onekq/OneSQL-v0.1-Qwen).

# Performances

The original model has an EX score of **63.33** on the [BIRD leaderboard](https://bird-bench.github.io/). Below is our self-evaluation for each quantization.

| Quantization |EX score|
|------------|------|
| Q2_K       | 47.78 |
| Q3_K_S     | 50.26 |
| Q3_K_M     | 51.50 |
| Q3_K_L     | 51.24 |
| Q4_1       | 46.54 |
| Q4_K_S     | 52.47 |
| **Q4_K_M** | **53.79** |
| Q5_0       | 50.23 |
| Q5_1       | 48.36 |
| Q5_K_S     | 51.93 |
| Q5_K_M     | 50.66 |
| Q6_K       | 52.89 |
| Q8_0       | 50.33 |

# Quick start

To use this model, craft your prompt to start with your database schema in the form of **CREATE TABLE**, followed by your natural language query preceded by **--**.
Make sure your prompt ends with **SELECT** in order for the model to finish the query for you. There is no need to set other parameters like temperature or max token limit.

```sh
PROMPT="CREATE TABLE students (
    id INTEGER PRIMARY KEY,
    name TEXT,
    age INTEGER,
    grade TEXT
);

-- Find the three youngest students
SELECT "

ollama run onekq-ai/OneSQL-v0.1-Qwen:32B-Q4_K_M "$PROMPT"
```

The model response is the finished SQL query without **SELECT**
```sql
* FROM students ORDER BY age ASC LIMIT 3
```
# Caveats

* The performance drop from the original model is due to quantization itself, and the lack of beam search support in llama.cpp framework. Use at your own discretion.
* The Q4_0 quantization suffers from repetitive output token, hence is not recommended for usage.