State-of-the-art advances in LLMs have pushed NLP to its limits, where even complex tasks, such as code generation, can be automated. This paper describes the deepSQL-R1-distill-8B, a fine-tuned and quantized model variant of the DeepSeek-R1 model architecture and specifically optimized for text-to-SQL conversion. Fine-tuning was performed using Unsloth, one of the most efficient frameworks for fine-tuning LLMs, in combination with Parameter-Efficient Fine-Tuning and the SFTTrainer framework. This allows domain-specific adaptation with minimal resource consumption. The approach fine-tunes curated datasets by LoRA, ensuring a more parameter-efficient and lower-memory-consuming model. Besides this, we investigate reinforcement learning techniques to further enhance the model’s ability in generating accurate and contextually appropriate SQL queries. Combination of 8-bit quantization, LoRA, Unsloth, and reinforcement learning places deepSQL-R1-distill-8B as one of the cutting-edge solutions for automatic SQL code generation in real-world applications. Addressing major challenges in computational efficiency, domain-specific adaptation, and reinforcement-based refinement, this model is…
Модальности:
Генерация текста
Области применения:
Диалог / чат Текст в SQL
Задача: Генерация текста
Автор: imsanjoykb
Теги: adapter-transformers, unsloth,, pytorch,, deepseek-R1,, inference-endpoint,, sql-code-generation,, conversational, en
Лайков: 4 | Загрузок: 9
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
