README.md

# Model Card for LLaMA-3-8B SQL Fine-Tuned Model

## Model Overview

This model is a fine-tuned version of the `unsloth/llama-3-8b-bnb-4bit` model, specifically adapted for SQL-related tasks using the `b-mc2/sql-create-context` dataset. It leverages the **PEFT (Parameter-Efficient Fine-Tuning)** library for efficient training and is optimized for **graph-ml** tasks.

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## Model Details

- **Base Model:** `unsloth/llama-3-8b-bnb-4bit`
- **Fine-Tuning Dataset:** `b-mc2/sql-create-context`
- **Model Type:** Fine-tuned language model for SQL generation and understanding.
- **Framework:** PEFT (Parameter-Efficient Fine-Tuning)
- **License:** [More Information Needed]
- **Developed by:** [More Information Needed]

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## Intended Use

### Direct Use
This model is designed for generating SQL queries from natural language prompts or contextual descriptions. It can be used directly for:
- SQL query generation
- Database interaction automation
- Educational tools for learning SQL

### Downstream Use
The model can be fine-tuned further for specific database schemas or integrated into larger applications such as:
- Database management systems
- Business intelligence tools
- Data analytics platforms

### Out-of-Scope Use
This model is not intended for:
- Non-SQL-related tasks
- Generating malicious or harmful SQL queries
- Use cases requiring high precision without human validation

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## Bias, Risks, and Limitations
- **Bias:** The model may inherit biases present in the training data, such as favoring certain SQL dialects or structures.
- **Risks:** Incorrect SQL generation could lead to data corruption or security vulnerabilities if used without validation.
- **Limitations:** Performance may vary across different database schemas or complex queries.

**Recommendations:** Always validate generated SQL queries before execution, especially in production environments.