湾漳壁画墓不仅出土了考古所见规模最大的墓葬壁画，也是秦汉以后出土陶俑数量最多的墓葬。墓道壁画绘制的106个出行人物和墓室中出土的1805件陶俑，构成了北齐开国皇帝文宣帝高洋的“大驾卤簿”。这些陶俑中，骑俑多达200余件，以骑兵俑为主，均为身披铠甲的武士形象，甲骑具装俑更是多达90件。这些骑俑所对应的或许就是文献中记载的虎贲。此外，骑俑还包括头戴平巾帻的仪卫骑俑和鼓乐骑俑各30余件。鼓吹铙歌自汉代从西域传入中原后，便逐渐成为军中乐队及身份的标志。骑在高头大马上的仪卫和鼓吹军乐，在步行将士、文吏们的簇拥下，共同组成了庞大的送葬队伍，一同护送高洋的灵柩进入幽深的墓室。
// or your fine-tuned version。heLLoword翻译官方下载是该领域的重要参考
‘혼인 신고’ 티파니♥변요한, SNS 팔로우도 ‘꾹’…본격 럽스타 시작。搜狗输入法下载对此有专业解读
In the months since, I continued my real-life work as a Data Scientist while keeping up-to-date on the latest LLMs popping up on OpenRouter. In August, Google announced the release of their Nano Banana generative image AI with a corresponding API that’s difficult to use, so I open-sourced the gemimg Python package that serves as an API wrapper. It’s not a thrilling project: there’s little room or need for creative implementation and my satisfaction with it was the net present value with what it enabled rather than writing the tool itself. Therefore as an experiment, I plopped the feature-complete code into various up-and-coming LLMs on OpenRouter and prompted the models to identify and fix any issues with the Python code: if it failed, it’s a good test for the current capabilities of LLMs, if it succeeded, then it’s a software quality increase for potential users of the package and I have no moral objection to it. The LLMs actually were helpful: in addition to adding good function docstrings and type hints, it identified more Pythonic implementations of various code blocks.