pip-sql-1.3b-GGUF
| Property | Value |
|---|---|
| Parameter Count | 1.35B |
| License | Apache 2.0 |
| Format | GGUF (Quantized) |
| Language | English |
What is pip-sql-1.3b-GGUF?
pip-sql-1.3b-GGUF is a quantized version of PipableAI's original SQL model, specifically designed for text-to-SQL conversion tasks. Built on the DeepSeek base model and optimized using GGUF quantization, this model achieves remarkable performance metrics that rival larger models, including GPT-3.5, particularly on easy and medium difficulty queries.
Implementation Details
The model employs a sophisticated training approach combining softmax cross entropy and a modified form of policy gradient along with Q loss, optimized in an EM setup. It has been trained on the PipableAI/pip-txt-to-sql-spider-bird-dataset and supports both PyTorch and JAX frameworks for inference.
- Specialized text-to-SQL generation capabilities
- Efficient GGUF quantization for improved deployment
- Supports multiple inference frameworks
- Comprehensive benchmark performance across difficulty levels
Core Capabilities
- Achieves 78.5% accuracy on easy SQL queries
- 57.5% accuracy on medium-difficulty queries
- 42.1% accuracy on hard queries
- Outperforms larger models in specific benchmarks
- Efficient schema-based SQL generation
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for achieving competitive performance with just 1.3B parameters, outperforming larger models like SQLCoder-7B and even GPT-3.5 in certain scenarios. Its efficient quantization makes it more accessible for deployment while maintaining high accuracy.
Q: What are the recommended use cases?
The model is ideal for converting natural language questions to SQL queries, particularly in scenarios requiring database schema understanding. It's especially effective for easy to medium-complexity queries and can be integrated into both PyTorch and JAX-based applications.
