基于 Qwen2.5-7B-Instruct 进行 QLoRA 微调的角色扮演对话模型，支持中英双语。训练数据为 PIPPA 数据集。 PIPPA 是一个大规模人机角色扮演对话数据集。训练样本从 16,832 条去重对话中提取，经过质量过滤和分层采样。同时使用了英文原文和中文译文来构建双语训练集。 — 模型继承了 PIPPA 数据集和基座模型 Qwen2.5-7B-Instruct 中存在的偏见。 — 训练 prompt 将回复限制在约 30 字以内，不适合长文本生成。 — 对于训练数据之外的人设或场景，角色一致性可能下降。 — Transformers: 5.12.1 — PEFT: 0.19.1 — TRL: 1.6.0 — PyTorch: 2.11.0+cu128 — Datasets: 5.0.0 — Tokenizers: 0.22.2 PIPPA (Personal Interaction Pairs between People and AI), a large-scale dataset of human-AI role-pla Training samples were extracted from 16,832 deduplicated dialogues with quality filtering and stratified sampling. Both English originals and Chinese translations were used to create a bilingual training set. — The model inherits biases present in the PIPPA dataset and the base Qwen2.5-7B-Instruct model. — Responses are constrained to ~30 Chinese characters (or equivalent) by the training prompt, making it unsuitable for long-form generation. — Character consistency may degrade with out-of-distribution personas or scenarios. — Transformers: 5.12.1 — PEFT: 0.19.1 — TRL: 1.6.0 — PyTorch: 2.11.0+cu128 — Datasets: 5.0.0 — Tokenizers: 0.22.2
Модальности:
Генерация текста
Области применения:
Диалог / чат Следование инструкциям
Задача: Генерация текста
Автор: CyberpunkLegend
Теги: qwen2, roleplay, character, dialogue, bilingual, qwen, qlora, peft
Лайков: 3 | Загрузок: 37
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
