bgglee/NL2SQL_finetuned

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:3.2BQuant:BF16Ctx Length:32kArchitecture:Transformer0.0K Warm

The bgglee/NL2SQL_finetuned model is a 3.2 billion parameter Llama-3.2-3B-Instruct based model fine-tuned for Natural Language to SQL (NL2SQL) tasks. It specializes in converting natural language queries into SQL commands, leveraging a self-correction mechanism. This model is optimized for accurate SQL generation from user prompts, making it suitable for database interaction applications.

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NL2SQL Fine-Tuned Model Overview

This model, bgglee/NL2SQL_finetuned, is a specialized large language model built upon the meta-llama/Llama-3.2-3B-Instruct architecture. It has been extensively fine-tuned to excel in Natural Language to SQL (NL2SQL) conversion tasks, enabling users to interact with databases using plain language.

Key Capabilities

  • Accurate SQL Generation: Converts natural language queries into precise SQL commands.
  • Self-Correction Mechanism: Incorporates a unique "self-correction with WRONG_IDS-before-Repair" method to enhance accuracy and robustness of generated SQL.
  • Optimized for Database Interaction: Specifically trained on datasets like bird_dev_1434ea.json to handle complex database schemas and queries.
  • Efficient Fine-tuning: Utilizes LoRA (Low-Rank Adaptation) for efficient fine-tuning, which is then merged into a full model for seamless deployment.

Good For

  • Building NL2SQL Applications: Ideal for developers creating tools that allow users to query databases without writing SQL.
  • Automating Data Retrieval: Can be integrated into systems requiring automated SQL generation from user input.
  • Enhancing User Experience: Provides a more intuitive way for non-technical users to access and analyze data.