SQLCoder 7B
SQLCoder 7B 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
- 2023-10-03
- Context
- 100k
- Parameters
- 7B
- Architecture
- Decoder Only
- Specialization
- general
- Training
- finetuned
About
SQLCoder 7B is a specialized large language model designed to translate natural language questions into SQL queries, making database interaction more accessible to non-technical users. It uses a transformer architecture and is fine-tuned from a Mistral-7B model, trained on a substantial dataset of 20,000 questions with distinct database schemas to ensure robust performance. The model supports complex queries including joins and aggregations, though it performs best on simpler, non-ratio-based questions. With its compact size of 7 billion parameters, SQLCoder 7B is suitable for use on consumer-grade hardware with adequate GPU memory. However, it should be used with read-only database access to avoid security risks, as it's not built for database administration tasks or preventing malicious queries. For enhanced performance, particularly for join operations, users are advised to consider the sqlcoder-7b-2 model.
SQLCoder 7B is a model in the SQLCoder family. The structured metadata tracks a 100k-token context window. No headline benchmark score is tracked for SQLCoder 7B 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.