+ July 31, 2025: Upload model to modelscope and huggingface. + July 30, 2025: Publish the paper to arxiv > Large language models (LLMs) have demonstrated strong performance in translating natural language questions into SQL > queries (Text-to-SQL). In contrast, small language models (SLMs) ranging from 0.5B to 1.5B parameters currently > underperform on Text-to-SQL tasks due to their limited logical reasoning capabilities. However, SLMs offer inherent > advantages in inference speed and suitability for edge deployment. To explore their potential in Text-to-SQL > applications, we leverage recent advancements in post-training techniques. Specifically, we used the open-source > SynSQL-2.5M dataset to construct two derived datasets: SynSQL-Think-916K for SQL generation and > SynSQL-Merge-Think-310K > for SQL merge revision. We then applied supervised fine-tuning and reinforcement learning-based post-training to the > SLM, followed by inference using a corrective self-consistency approach. Experimental results validate the > effectiveness > and generalizability of our method, SLM-SQL. On the BIRD development set, the five evaluated models achieved an > average > improvement of 31.4…
Модальности:
Генерация текста
Области применения:
Текст в SQL Диалог / чат
Задача: Генерация текста
Автор: cycloneboy
Теги: qwen2, text-to-sql, reinforcement-learning, conversational, text-generation-inference, endpoints_compatible
Лайков: 3 | Загрузок: 44
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
