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---
license: apache-2.0
datasets:
- VPCSinfo/odoo-sql-query-dataset
base_model:
- defog/sqlcoder-7b-2
pipeline_tag: text-generation
library_name: adapter-transformers
tags:
- code
---
# Fine-Tuned SQLCoder-7B for Odoo 17
This is a fine-tuned version of [defog/sqlcoder-7b-2](https://huggingface.co/defog/sqlcoder-7b-2) trained on Odoo 17 database schemas and queries.
## Model Details
- Base model: defog/sqlcoder-7b-2
- Fine-tuned using LoRA for parameter-efficient adaptation
- Optimized for Odoo 17 SQL queries
## Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
# Load the model with PEFT adapter
model = AutoModelForCausalLM.from_pretrained("VPCSinfo/odoo17-sqlcoder-7b")
tokenizer = AutoTokenizer.from_pretrained("VPCSinfo/odoo17-sqlcoder-7b")
# Example query
schema = """
CREATE TABLE res_partner (
id INTEGER PRIMARY KEY,
name VARCHAR(255),
email VARCHAR(255),
phone VARCHAR(64)
);
CREATE TABLE sale_order (
id INTEGER PRIMARY KEY,
partner_id INTEGER REFERENCES res_partner(id),
date_order TIMESTAMP,
state VARCHAR(20),
amount_total NUMERIC
);
"""
question = "Find all customers who have orders with a total amount greater than 1000"
# Format your input following SQLCoder's expected format
prompt = f'''### Task
Generate a SQL query to answer the question below based on the table schema.
### Database Schema
CREATE TABLE res_partner (
id INTEGER PRIMARY KEY,
name VARCHAR(255),
email VARCHAR(255),
phone VARCHAR(64)
);
CREATE TABLE sale_order (
id INTEGER PRIMARY KEY,
partner_id INTEGER REFERENCES res_partner(id),
date_order TIMESTAMP,
state VARCHAR(20),
amount_total NUMERIC
);
### Question
Find all customers who have orders with a total amount greater than 1000
### SQL Query
'''
# Generate SQL
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=300)
sql_query = tokenizer.decode(outputs[0], skip_special_tokens=True).split("### SQL Query")[1].strip()
print(sql_query) |