Qwen3.8-27B-Humanlike-Chat: A model I tuned to imitate realistic human-to-human conversation
一位开发者创建了Qwen3.8-27B-Humanlike-Chat模型，旨在模仿真实的人际对话，以解决大型语言模型常见的“AI助手”风格。该模型基于huihui-ai/Huihui-Qwen3.8-27B-abliterated，通过rank-256 LoRA进行训练，发布的版本是checkpoint 863。其目标是提供更短、更不雕琢、更像人类的回复，尤其是在随意对话中，即使没有系统提示也能实现。
为什么是这条该模型不同于多数LLM的“AI助手”风格，旨在提供更像人类、更不雕琢的对话回复，即便没有系统提示也能实现。
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发布当时偏移：UTC+02026年9月11日 16:27 UTC
收录当时偏移：UTC+02026年9月12日 15:01 UTC
- 发布
- 2026年9月11日 16:27
- 收录
- 2026年9月12日 15:01
- 来源类型
- 开发者社区
- 档位
- 社区
- 信源状态
- 正常
档位是按信源手工设定的编辑判断，不是逐条打分。
I made this because I was getting genuinely annoyed at trying to have a normal conversation with LLMs. Even with prompting and various tricks, most models I've tried still have this "AI assistant" vibe to them that is so familiar: too helpful, polished, verbose, using words we never use in conversation, etc.
I wanted a model that could just talk to me like a person, so I did the slightly unreasonable thing and put together a dataset and trained one.
The dataset used for training is 125,217 obfuscated human-to-human messages across 1396 chat conversations.
The goal wasn't to make Qwen smarter or improve benchmark scores. I was trying to change its conversational habits, to make it stop turning every reply into an explanation, agreeing with everything, and writing stuff just to keep the conversation "going".
I trained a rank-256 LoRA on top of huihui-ai/Huihui-Qwen3.8-27B-abliterated. The released version is checkpoint 863. In my testing it feels noticeably less like an assistant, particularly in casual conversations, even without a system prompt. Replies are generally shorter, less polished, and, well, more human.
There may be a tradeoff. An earlier iteration scored five percentage points lower than its Huihui parent on IFEval, an instruction-following benchmark. I haven't rerun that benchmark on this version of the checkpoint, and I haven't tested coding performance, so I don't want to pretend that number applies here.
I've added a side-by-side comparison using the same system prompt, user messages, and generation settings for both models. Each model continued its own conversation branch, with reasoning effort set to 'xhigh'.
Space where you can have a demo chat with different system prompts and reasoning modes: