Introducing the latest fine-tuned version of Qwen2.5-Coder-14B-Instruct, specifically tailored for SQL code generation. Built on the robust 14-billion parameter Qwen2.5-Coder architecture, this model leverages advanced configurations like bfloat16 precision and a custom quantization setup, optimized for efficient 4-bit computation. With a maximum context window of 32K tokens, this model supports extensive SQL sequences and complex query generation without compromising accuracy or performance. Our fine-tuning process has enriched this model with domain-specific SQL patterns and nuanced query constructions, making it exceptionally adept at handling real-world SQL requirements, from query creation to debugging and optimization. By combining Qwen2.5’s foundational strengths with targeted training on custom SQL data, this model achieves a powerful balance of general-purpose code understanding and SQL-specific precision, making it an ideal tool for developers and data engineers seeking top-tier SQL generation capabilities. Here provides a code snippet with applychattemplate to show you how to load the tokenizer and model and how to generate contents.
Модальности:
Генерация текста
Области применения:
Диалог / чат Генерация кода Текст в SQL
Задача: Генерация текста
Автор: imsanjoykb
Теги: adapter-transformers, unsloth,, pytorch,, inference-endpoint,, sql-code-generation,, conversational, en
Лайков: 3 | Загрузок: 21
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
