SQLCoder 2
SQLCoder 2 has model metadata, but missing tracked provider pricing keeps it from being a default production pick.
Use it for
- Teams evaluating general LLM work
- Workloads that can use a 100k context window
Do not use it for
- Cost-sensitive launches that need sourced token pricing
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
- Family
- SQLCoder
- Released
- 2023-10-02
- Context
- 100k
- Parameters
- 15B
- Architecture
- Decoder Only
- Specialization
- general
- Training
- finetuned
About
SQLCoder 2 is an advanced large language model developed by Defog AI that specializes in transforming natural language questions into SQL queries. It outperforms models like GPT-3.5-turbo and GPT-4 (when fine-tuned on specific schemas) in delivering precise SQL code from natural language inputs. Based on the 15B parameter StarCoder model, SQLCoder 2 is trained on over 20,000 human-curated questions across various database schemas, making it adept at executing complex queries involving joins, aggregations, and date filtering. This model empowers non-technical users to perform data analysis in SQL databases, facilitating self-service analytics without the need for SQL expertise. SQLCoder 2 is available on the Hugging Face platform and includes a user-friendly demo on the Defog website 234.
SQLCoder 2 is a proprietary model in the SQLCoder family. The structured metadata tracks a 100k-token context window. No headline benchmark score is tracked for SQLCoder 2 yet.
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
No tracked provider token pricing is available for this model yet.
Capabilities
No model capability flags are currently sourced.
Benchmark peer barsfor Coding
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.