metadata
language: en
tags:
- sql
- code-generation
- reinforcement-learning
- text-generation
datasets:
- spider
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)