SQLCoder 34B Alpha
SQLCoder 34B Alpha 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
- 2023-11-14
- Context
- 100k
- Parameters
- 34B
- Architecture
- Decoder Only
- Specialization
- general
- Training
- finetuned
About
SQLCoder-34B Alpha is an advanced large language model developed by Defog.ai, designed to transform natural language questions into SQL queries. With 34 billion parameters, it excels in natural language-to-SQL conversion tasks, significantly outperforming models like GPT-4. The model is based on the Llama architecture and fine-tuned on the CodeLlama base. Trained on over 20,000 human-curated questions across diverse database schemas, it ensures robust performance by not using the same schemas for evaluation. Its capabilities include high accuracy in generating SQL queries with various clauses, although performance varies by query type. Accessible through the Hugging Face library, it offers an easy-to-use interface for business users and data analysts, despite requiring substantial computational resources to run.
SQLCoder 34B Alpha is a model in the SQLCoder family. The structured metadata tracks a 100k-token context window. No headline benchmark score is tracked for SQLCoder 34B Alpha 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.