> Update: > This model has been further enhanced with additional reasoning data distilled from Qwen3.5-27B. > > The new training data introduces higher-quality reasoning trajectories across domains such as science, instruction-following, and mathematics. > > Part of the data comes from Jackrong/Qwen3.5-reasoning-700x, a curated dataset designed to improve structured step-by-step reasoning and reasoning diversity. Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled is a highly capable reasoning model fine-tuned on top of the Qwen3.5-9B dense architecture. The model’s core directive is to leverage state-of-the-art Chain-of-Thought (CoT) distillation primarily sourced from Claude-4.6 Opus interactions. Through Supervised Fine-Tuning (SFT) focusing specifically on structured reasoning logic, this model excels in breaking down complex user problems, planning step-by-step methodologies within strictly formatted tags, and ultimately delivering precise, nuanced solutions. The model includes targeted optimizations addressing Qwen3.5’s tendency toward excessive transitional or repetitive reasoning on simple queries. Through deep distillation and structural imitation of Claude-4.6-Opus reasoning…
Модальности:
Генерация текста
Области применения:
Логика и рассуждение Диалог / чат
Задача: Генерация текста
Автор: icecee
Теги: qwen3_5, unsloth, qwen, qwen3.5, reasoning, chain-of-thought, lora, conversational
Лайков: 3 | Загрузок: 59
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
