ghzllghe/qwen2.5-7b-text2sql-lora-v2
TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 5, 2026Architecture:Transformer Featherless Exclusive Cold
The ghzllghe/qwen2.5-7b-text2sql-lora-v2 is a 7.6 billion parameter language model, likely based on the Qwen2.5 architecture, fine-tuned for text-to-SQL generation. This model specializes in converting natural language queries into executable SQL commands, making it highly effective for database interaction tasks. Its 32K context length supports complex query understanding and generation.
Loading preview...
Model Overview
The ghzllghe/qwen2.5-7b-text2sql-lora-v2 is a specialized language model, likely built upon the Qwen2.5 architecture, featuring 7.6 billion parameters and a substantial 32,768 token context window. This model has been fine-tuned using LoRA (Low-Rank Adaptation) specifically for text-to-SQL tasks.
Key Capabilities
- Natural Language to SQL Conversion: Excels at translating human language questions into precise SQL queries.
- Large Context Window: The 32K context length allows for processing complex and detailed natural language inputs, improving the accuracy of generated SQL.
- LoRA Fine-tuning: Utilizes an efficient fine-tuning method, suggesting potential for adaptability and efficient deployment.
Good for
- Database Interaction: Ideal for applications requiring users to query databases using natural language without needing SQL expertise.
- Automated Report Generation: Can be integrated into systems to generate data reports based on user prompts.
- Data Analysis Tools: Enhancing user interfaces for data exploration by enabling natural language queries.