jastorj/couchmind-v5.7.8.1_arctic_stage_3-cw-24K-16bit
jastorj/couchmind-v5.7.8.1_arctic_stage_3-cw-24K-16bit is a 7.6 billion parameter model fine-tuned by jastorj from Snowflake/Arctic-Text2SQL-R1-7B. This model specializes in Text-to-SQL generation for Couchbase SQL++ queries, leveraging the NL2SQL++ v5.7.8.1_arctic_stage_3 dataset with code-with-thought reasoning. It is optimized for accurately translating natural language questions into syntactically valid SQL++ queries, including error analysis and refinement capabilities.
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Model Overview
This model, jastorj/couchmind-v5.7.8.1_arctic_stage_3-cw-24K-16bit, is a specialized fine-tuned version of the Snowflake/Arctic-Text2SQL-R1-7B base model. Developed by jastorj, it focuses on Text-to-SQL generation specifically for Couchbase SQL++ queries.
Key Capabilities
- Couchbase SQL++ Generation: Translates natural language questions into precise and syntactically valid Couchbase SQL++ queries.
- Schema Awareness: Utilizes provided database schema (including bucket, scope, and collection names) to generate accurate queries.
- Error Analysis and Refinement: Demonstrates the ability to analyze SQL++ query errors (e.g., identifier errors) and provide refined, corrected queries.
- Code-with-Thought Reasoning: Fine-tuned on a dataset that includes reasoning steps, enhancing its ability to understand and correct complex SQL issues.
- LoRA Fine-tuning: Employs Low-Rank Adaptation (LoRA) with Unsloth for efficient fine-tuning, resulting in 16-bit merged weights.
Ideal Use Cases
This model is particularly well-suited for applications requiring:
- Automated generation of Couchbase SQL++ queries from natural language inputs.
- Assisting developers or data analysts in writing correct SQL++ queries, especially when dealing with complex schemas or common syntax errors.
- Building intelligent interfaces for Couchbase databases where users can query data using plain English.