---
title: sqlcoder-7b-2
canonical_url: "https://www.modelscope.cn/models/AI-ModelScope/sqlcoder-7b-2"
md_url: "https://www.modelscope.cn/models/AI-ModelScope/sqlcoder-7b-2.md"
repository: AI-ModelScope/sqlcoder-7b-2
last_updated: 2024-04-25
license: cc-by-sa-4.0
pipeline_tag: text-generation
tasks:
  - text-generation
model_type:
  - llama
architectures:
  - LlamaForCausalLM
parameters: 6.7B
tensor_type:
  - F16
library_name:
  - safetensors
  - gguf
  - pytorch
frameworks:
  - pytorch
inference_backends:
  - "deploy_task text/emb"
  - "lmdeploy 0.9.1"
  - "lmdeploy_turbomind 0.9.1"
  - "sglang 0.5.2"
  - "vllm 0.9.2"
downloads: 5607
stars: 20
tags:
  - gguf
---

# sqlcoder-7b-2

> sqlcoder-7b-2 - AI-ModelScope 在 ModelScope 开源的模型。Update notice The model weights were updated at 7 AM UTC on Feb 7, 2024. The new model weights lead to a much more performant model – particularly for joins.

AI-ModelScope/sqlcoder-7b-2 是 ModelScope 魔搭社区上的 6.7B 参数text-generation模型，采用 cc-by-sa-4.0 许可，可用 deploy_task text/emb、lmdeploy 0.9.1、lmdeploy_turbomind 0.9.1 部署。

- **Repository**: AI-ModelScope/sqlcoder-7b-2
- **License**: cc-by-sa-4.0
- **Tasks**: text-generation
- **Parameters**: 6.7B
- **Inference backends**: deploy_task text/emb, lmdeploy 0.9.1, lmdeploy_turbomind 0.9.1, sglang 0.5.2, vllm 0.9.2
- **Tags**: gguf
- **Downloads**: 5607
- **Stars**: 20
- **Last updated**: 2024-04-25

Source: https://www.modelscope.cn/models/AI-ModelScope/sqlcoder-7b-2

---

# Update notice
The model weights were updated at 7 AM UTC on Feb 7, 2024. The new model weights lead to a much more performant model – particularly for joins.

If you downloaded the model before that, please redownload the weights for best performance.

# Model Card for SQLCoder-7B-2

A capable large language model for natural language to SQL generation.

![image/png](https://cdn-uploads.huggingface.co/production/uploads/603bbad3fd770a9997b57cb6/AYUE2y14vy2XkD9MZpScu.png)

## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** [Defog, Inc](https://defog.ai)
- **Model type:** [Text to SQL]
- **License:** [CC-by-SA-4.0]
- **Finetuned from model:** [CodeLlama-7B]

### Model Sources [optional]
- [**HuggingFace:**](https://huggingface.co/defog/sqlcoder-70b-alpha)
- [**GitHub:**](https://github.com/defog-ai/sqlcoder)
- [**Demo:**](https://defog.ai/sqlcoder-demo/)

## Uses

This model is intended to be used by non-technical users to understand data inside their SQL databases. It is meant as an analytics tool, and not as a database admin tool.

This model has not been trained to reject malicious requests from users with write access to databases, and should only be used by users with read-only access.

## How to Get Started with the Model

Use the code [here](https://github.com/defog-ai/sqlcoder/blob/main/inference.py) to get started with the model.

## Prompt

Please use the following prompt for optimal results. Please remember to use `do_sample=False` and `num_beams=4` for optimal results.

```
### Task
Generate a SQL query to answer [QUESTION]{user_question}[/QUESTION]

### Database Schema
The query will run on a database with the following schema:
{table_metadata_string_DDL_statements}

### Answer
Given the database schema, here is the SQL query that [QUESTION]{user_question}[/QUESTION]
[SQL]
```

## Evaluation

This model was evaluated on [SQL-Eval](https://github.com/defog-ai/sql-eval), a PostgreSQL based evaluation framework developed by Defog for testing and alignment of model capabilities.

You can read more about the methodology behind SQLEval [here](https://defog.ai/blog/open-sourcing-sqleval/).

### Results

We classified each generated question into one of 6 categories. The table displays the percentage of questions answered correctly by each model, broken down by category.

|                | date | group_by | order_by | ratio | join | where |
| -------------- | ---- | -------- | -------- | ----- | ---- | ----- |
| sqlcoder-70b   | 96   | 91.4     | 97.1     | 85.7  | 97.1 | 91.4  |
| sqlcoder-7b-2  | 96   | 91.4     | 94.3     | 91.4  | 94.3 | 77.1  |
| sqlcoder-34b   | 80   | 94.3     | 85.7     | 77.1  | 85.7 | 80    |
| gpt-4          | 72   | 94.3     | 97.1     | 80    | 91.4 | 80    |
| gpt-4-turbo    | 76   | 91.4     | 91.4     | 62.8  | 88.6 | 77.1  |
| natural-sql-7b | 56   | 88.6     | 85.7     | 60    | 88.6 | 80    |
| sqlcoder-7b    | 64   | 82.9     | 74.3     | 54.3  | 74.3 | 74.3  |
| gpt-3.5        | 72   | 77.1     | 82.8     | 34.3  | 65.7 | 71.4  |
| claude-2       | 52   | 71.4     | 74.3     | 57.1  | 65.7 | 62.9  |

## Model Card Contact

Contact us on X at [@defogdata](https://twitter.com/defogdata), or on email at [founders@defog.ai](mailto:founders@defog.ai)