ArityFlow-Qwen3-4B-Instruct-2507-RolePlay

ArityFlow-Qwen3-4B-Instruct-2507-RolePlay

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English | 中文

A RolePlay-oriented fine-tuning based on Qwen3-4B-Instruct-2507

一个专注于沉浸式角色扮演（RolePlay）的 Qwen3 微调模型

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📖 Overview | 模型简介

🇺🇸 English

ArityFlow-Qwen3-4B-Instruct-2507-RolePlay is a RolePlay-focused fine-tuned model based on Qwen3-4B-Instruct-2507.

Unlike general-purpose instruction tuning, this project focuses on improving:

• Character consistency
• Emotional expression
• Story progression
• Long-form dialogue
• Fantasy world building
• Immersive roleplay

The model was trained using QLoRA (NF4) with MS-SWIFT.

This repository contains:

• ✅ Merged Full Model (Recommended)
• ✅ Original LoRA Adapter (/lora)

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🇨🇳 中文

ArityFlow-Qwen3-4B-Instruct-2507-RolePlay 是基于 Qwen3-4B-Instruct-2507 微调得到的角色扮演模型。

本项目并非以 Benchmark 为主要目标，而是重点提升：

• 人设一致性
• 情绪表达
• 剧情推进
• 长对话能力
• 世界观构建
• 沉浸式角色扮演体验

模型采用 MS-SWIFT + QLoRA(NF4) 完成训练。

本仓库同时提供：

• ✅ 合并后的完整模型（推荐直接推理）
• ✅ 原始 LoRA Adapter（位于 /lora）

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✨ Features | 模型特点

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📦 Repository Structure | 仓库结构

.
├── README.md
├── config.json
├── generation_config.json
├── tokenizer.json
├── tokenizer_config.json
├── special_tokens_map.json
├── model.safetensors...
│
└── lora/
    ├── adapter_model.safetensors
    ├── adapter_config.json
    ├── args.json
    └── ...

Root directory

Merged Full Model

lora/

Original QLoRA Adapter

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⚙️ Training Configuration | 训练配置

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📚 Dataset | 数据集

The model was trained on a merged ShareGPT-format RolePlay dataset.

训练数据采用 ShareGPT 格式角色扮演数据。

After filtering samples longer than 4096 tokens:

过滤超过 4096 Token 的样本后：

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📈 Training Result | 训练结果

Training converged smoothly without obvious overfitting.

训练过程收敛稳定，无明显过拟合。

Final Validation Token Accuracy

最终验证集 Token Accuracy

64.41%

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🔍 Qualitative Evaluation | 主观测试

The model was manually compared against the original Qwen3 model using identical prompts and generation parameters.

在完全相同的 Prompt 与采样参数下，对 Base Qwen3 与微调模型进行了人工对比测试。

Observed improvements:

• Better character consistency
• Richer action descriptions
• Better emotional expression
• Better environmental descriptions
• Stronger fantasy world building
• Better NPC generation
• Better long-form roleplay

观察到的提升：

• 更稳定的人设保持
• 更丰富的动作描写
• 更自然的情绪表达
• 更好的环境描写
• 更完整的幻想世界构建
• 更自然的 NPC 生成
• 更好的长剧情角色扮演体验

The merged model was compared against the original LoRA adapter and showed no observable degradation during manual testing.

同时对 LoRA Adapter 与合并后的完整模型进行了人工对比，未观察到明显的生成质量下降。

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💬 Example | 示例

System Prompt

You are Bai Zhi.

The librarian of the Imperial Royal Library.

Stay in character.

Never reveal yourself as an AI.

Maintain the fantasy world setting.

User

The library has already closed.

Heavy rain is falling outside.

I push open the old wooden door and see you repairing an ancient book beside a candle.

"So late... why aren't you going home?"

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🚀 Usage | 使用方式

Transformers

from transformers import AutoTokenizer
from transformers import AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("YOUR_MODEL")

model = AutoModelForCausalLM.from_pretrained(
    "YOUR_MODEL",
    torch_dtype="auto",
    device_map="auto"
)

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MS-SWIFT

Merged Model

swift infer \
    --model YOUR_MODEL_PATH

LoRA Adapter

swift infer \
    --model Qwen/Qwen3-4B-Instruct-2507 \
    --adapters lora/

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🎯 Recommended Use Cases | 推荐使用场景

Recommended

• RolePlay
• Character Chat
• Interactive Fiction
• Fantasy Dialogue
• NPC Generation
• Storytelling

推荐：

• 角色扮演
• 剧情互动
• 长剧情聊天
• 世界观构建
• NPC 对话
• 小说式聊天

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⚠️ Limitations | 已知特点

Compared with the original Qwen3 model, this model intentionally produces:

• Longer responses
• Richer descriptions
• Stronger emotions
• More proactive story progression

This behavior is expected and is part of the design objective.

相较于基础模型，本模型会：

• 回复更长
• 动作描写更多
• 环境描写更多
• 情绪表达更丰富
• 更倾向主动推进剧情

这是本项目有意优化的方向，并非异常行为。

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🙏 Acknowledgements | 致谢

This project is built upon the following open-source projects:

• Alibaba Qwen Team
• MS-SWIFT
• Hugging Face Transformers
• PEFT
• ModelScope

Special thanks to the open-source community.

本项目基于以下优秀开源项目完成：

• Alibaba Qwen Team
• MS-SWIFT
• Hugging Face Transformers
• PEFT
• ModelScope

感谢所有开源贡献者。

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📄 License | 许可证

This model follows the license of the original Qwen3-4B-Instruct-2507.

Please refer to the original license before commercial use.

本模型遵循 Qwen3-4B-Instruct-2507 的许可证。

商业使用前请阅读原始模型许可证。