OGSQL-Mistral7B
Model Description
OGSQL-Mistral7B was fine-tuned for the task of converting natural language text into SQL queries.
- Model type: Mixture Of Experts (MoE)
- Language(s) (NLP): SQL (target language for generation)
- Finetuned from model: Mistral 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
# Example code to load and use the model
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
model_name = "OGSQL-Mistral7B"
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:
