jastorj/couchmind-v5.7.6.1_arctic_stage_2-cw-12K-16bit
The jastorj/couchmind-v5.7.6.1_arctic_stage_2-cw-12K-16bit model is a 7.6 billion parameter language model, fine-tuned by jastorj from Snowflake's Arctic-Text2SQL-R1-7B. It specializes in Text-to-SQL generation for Couchbase SQL++ queries, leveraging the NL2SQL++ v5.7.6.1_arctic_stage_2 dataset with code-with-thought reasoning. This model is optimized for accurately translating natural language questions into syntactically valid SQL++ queries, making it ideal for database interaction and data retrieval tasks.
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Overview
This model, jastorj/couchmind-v5.7.6.1_arctic_stage_2-cw-12K-16bit, is a specialized 7.6 billion parameter language model derived from Snowflake/Arctic-Text2SQL-R1-7B. It has been meticulously fine-tuned for Text-to-SQL generation, specifically targeting Couchbase SQL++ queries.
Key Capabilities
- Precise SQL++ Generation: Translates natural language questions into syntactically valid Couchbase SQL++ queries.
- Schema Awareness: Utilizes provided database schemas (bucket, scope, collection names, field types) to generate accurate queries.
- Code-with-Thought Reasoning: Fine-tuned on the NL2SQL++ v5.7.6.1_arctic_stage_2 dataset, which incorporates a "code-with-thought" reasoning approach to enhance query accuracy.
- Optimized for Couchbase: Designed to adhere to Couchbase SQL++ syntax and conventions, including explicit bucket, scope, and collection naming.
- Efficient Fine-tuning: Leverages LoRA (Low-Rank Adaptation) with Unsloth for efficient training, resulting in 16-bit merged weights.
Good For
- Automated Database Interaction: Ideal for applications requiring automated generation of SQL++ queries from user input.
- Data Retrieval: Facilitates natural language querying of Couchbase databases.
- Developer Tools: Can be integrated into tools that assist developers in writing complex SQL++ queries.
- Educational Purposes: Useful for demonstrating Text-to-SQL capabilities within the Couchbase ecosystem.