Text2sql 1.5B

🚀 Text2SQL-1.5B模型

Text2SQL-1.5B 是一款强大的 自然语言转SQL 模型，旨在将用户查询转换为结构化的SQL语句。它支持复杂的多表查询，并确保在文本到SQL的转换中具有较高的准确性。

🚀 快速开始

系统指令

为确保模型输出的一致性，请使用以下系统指令：

始终将代码和解释分开。将SQL代码放在单独的代码块中，随后在单独的段落中进行解释。使用Markdown的三个反引号（```sql 用于SQL）正确格式化代码。先在单独的代码块中编写SQL查询，然后用纯文本解释该查询。不要将它们合并为一个响应。

对于JSON结果，请使用以下指令：

始终将SQL代码和解释分开。以包含两个键（'query' 和 'explanation'）的JSON格式返回SQL查询。响应应严格遵循以下结构：{"query": "SQL_QUERY_HERE", "explanation": "EXPLANATION_HERE"}。'query' 键应仅包含SQL语句，'explanation' 键应提供对查询的纯文本解释。不要将它们合并为一个响应。

提示格式

提示格式应同时包含用户查询和使用 CREATE TABLE 语句的表结构。预期的消息格式如下：

messages = [
    {"role": "system", "content": "Always separate code and explanation. Return SQL code in a separate block, followed by the explanation in a separate paragraph. Use markdown triple backticks (```sql for SQL) to format the code properly. Write the SQL query first in a separate code block. Then, explain the query in plain text. Do not merge them into one response. The query should always include the table structure using a CREATE TABLE statement before executing the main SQL query."},
    {"role": "user", "content": "Show the total sales for each customer who has spent more than $50,000."},
    {"role": "user", "content": "
CREATE TABLE sales (
    id INT PRIMARY KEY,
    customer_id INT,
    total_amount DECIMAL(10,2),
    FOREIGN KEY (customer_id) REFERENCES customers(id)
);

CREATE TABLE customers (
    id INT PRIMARY KEY,
    name VARCHAR(255)
);
"}
] 

模型使用

💻 使用示例

基础用法

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

# Load tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("yasserrmd/Text2SQL-1.5B")
model = AutoModelForCausalLM.from_pretrained("yasserrmd/Text2SQL-1.5B")

# Define the pipeline
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

# Define system instruction
system_instruction = "Always separate code and explanation. Return SQL code in a separate block, followed by the explanation in a separate paragraph. Use markdown triple backticks (```sql for SQL) to format the code properly. Write the SQL query first in a separate code block. Then, explain the query in plain text. Do not merge them into one response. The query should always include the table structure using a CREATE TABLE statement before executing the main SQL query."

# Define user query
user_query = "Show the total sales for each customer who has spent more than $50,000.
CREATE TABLE sales (
    id INT PRIMARY KEY,
    customer_id INT,
    total_amount DECIMAL(10,2),
    FOREIGN KEY (customer_id) REFERENCES customers(id)
);

CREATE TABLE customers (
    id INT PRIMARY KEY,
    name VARCHAR(255)
);
"

# Define messages for input
messages = [
    {"role": "system", "content": system_instruction},
    {"role": "user", "content": user_query},
]

# Generate SQL output
response = pipe(messages)


# Print the generated SQL query
print(response[0]['generated_text'])

📦 安装指南

文档未提供安装步骤，暂不展示。

📚 详细文档

上传的模型

• 开发者：yasserrmd
• 许可证：apache-2.0
• 微调自的模型：unsloth/qwen2.5-coder-1.5b-instruct-bnb-4bit

这个Qwen2模型使用 Unsloth 和Huggingface的TRL库进行训练，速度提高了2倍。

📄 许可证

本模型使用的许可证为 apache-2.0。

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