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---
license: cc-by-4.0
language:
- en
tags:
- Text-to-sql
---
# OGSQL-7B
### Model Description
OGSQL-7B was fine-tuned for the task of converting natural language text into SQL queries.
- **Model type**: Transformer
- **Language(s) (NLP)**: SQL (target language for generation)
- **Finetuned from model**: gemma 7b instruct
## Use Case
OGSQL-7B is designed to facilitate the conversion of natural language queries into structured SQL commands, aiding in database querying without the need for manual SQL knowledge.
## How to Get Started with the Model
```python
# Example code to load and use the model
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
model_name = "OGSQL-7B"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
def generate_sql(query):
inputs = tokenizer.encode(query, return_tensors="pt")
outputs = model.generate(inputs)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
# Example use
query = """
using this context:
-- Create Customers Table
CREATE TABLE Customers (
customer_id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
email TEXT,
join_date DATE
);
-- Create Products Table
CREATE TABLE Products (
product_id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
price DECIMAL(10, 2)
);
-- Create Orders Table
CREATE TABLE Orders (
order_id INTEGER PRIMARY KEY,
customer_id INTEGER,
product_id INTEGER,
order_date DATE,
quantity INTEGER,
total_price DECIMAL(10, 2),
FOREIGN KEY (customer_id) REFERENCES Customers(customer_id),
FOREIGN KEY (product_id) REFERENCES Products(product_id)
);
show me all the orders from last month , sort by date
"""
print(generate_sql(query))
```
## alternatively you can use this notebook:
[](https://colab.research.google.com/drive/1zfuzV3R1GQflHV_va03WArb8vhwPh_2T)
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