metadata

license: mit
datasets:
  - b-mc2/sql-create-context
language:
  - en
  - id
base_model:
  - meta-llama/Llama-3.2-1B
tags:
  - SQL
  - Llama
  - guff

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.

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]

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

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.