微调 Qwen 2.5 3B 以生成逼真的电影对话
Fine-Tuning Qwen 2.5 3B for Realistic Movie Dialogue Generation
AI总结：
本文微调 Qwen 2.5 3B 模型，利用康奈尔电影对话语料库生成逼真电影对话，通过从 0.5B 逐步扩展至 3B 克服计算限制，证明小型模型在实时上下文对话生成中的潜力。
摘要：
Qwen 2.5 3B 基础模型被微调以生成上下文丰富且引人入胜的电影对话，利用了康奈尔电影对话语料库（Cornell Movie-Dialog Corpus），这是一个经过整理的电影对话数据集。由于 GPU 计算能力和显存（VRAM）的限制，训练过程从 0.5B 模型开始，随着效率改进的实施，逐步扩展到 1.5B 和 3B 版本。由阿里巴巴集团开发的 Qwen 2.5 系列处于小型开源预训练模型的前沿，特别是在创意任务中，与 Meta 的 Llama 3.2 和 Google 的 Gemma 等替代模型相比表现出色。结果表明，小型模型能够生成高质量、逼真的对话，为实时、上下文敏感的对话生成提供了一种有前景的方法。
英文摘要：
The Qwen 2.5 3B base model was fine-tuned to generate contextually rich and engaging movie dialogue, leveraging the Cornell Movie-Dialog Corpus, a curated dataset of movie conversations. Due to the limitations in GPU computing and VRAM, the training process began with the 0.5B model progressively scaling up to the 1.5B and 3B versions as efficiency improvements were implemented. The Qwen 2.5 series, developed by Alibaba Group, stands at the forefront of small open-source pre-trained models, particularly excelling in creative tasks compared to alternatives like Meta's Llama 3.2 and Google's Gemma. Results demonstrate the ability of small models to produce high-quality, realistic dialogue, offering a promising approach for real-time, context-sensitive conversation generation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
