“百聆”是一个基于LLaMA的语言对齐增强的英语/中文大语言模型，具有优越的英语/中文能力，在多语言和通用任务等多项测试中取得ChatGPT 90%的性能。BayLing is an English/Chinese LLM equipped with advanced language alignment, showing superior capability in English/Chinese generation, instruction following and multi-turn interaction.
Home Page: http://nlp.ict.ac.cn/bayling
License: GNU General Public License v3.0
如题：微信群求拉进，二维码失效了
{"src": "Could you please try to make a purchase on the computer on the website.", "tgt": "请您试着使用电脑从网站购买。", "constraint": ["电脑从", "试着使用", "请您"], "hypo": "请您在电脑上尝试从网站上进行购买。"}
测试下来发现：中文的输出还是带有英式中文的痕迹，但总体来说效果还行。观察到一些数据样例，发现翻译对的约束项似乎是标准译文的随机分割。这和论文中的 Ch 3. 的展示内容有些出入。是否实际训练时这种对于模型的约束并不强？有相关分析吗？
Any plan to opensource sft data?
这个模型是一个lora模型？为什么要加载一个LLaMA模型作底模？
求新的微信群谢谢
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