Model Card for RL-GRPO-SQL-Model

Model Details

Model Description

• Model type: Fine-tuned Causal Language Model with Reinforcement Learning
• Training approach: Reinforcement Learning with GRPO (Group Relative Policy Optimization)
• Task: SQL generation and understanding
• Developed by: Ali Assi

Training Data

• Data sources: Spider train set
• Preprocessing: Parsing and validation
• Languages: English

How to Use

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ALI-USER/rl-grpo-sql-model")
model = AutoModelForCausalLM.from_pretrained("ALI-USER/rl-grpo-sql-model")

# Example usage
prompt = "Generate SQL for: Find all customers with orders over $100"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=512)
print(tokenizer.decode(outputs[0]))

Limitations

• Model performance may vary depending on database schema complexity

Ethical Considerations

• May generate SQL queries that are inefficient or unsafe if not properly validated
• Should be used with query validation before execution

Intended Uses

Primary use cases:

• Natural language to SQL translation
• SQL code generation assistance
• Educational purposes for SQL understanding

Out-of-scope uses:

• Direct production deployment without query validation
• Non-English language queries (not trained for this)