基于 Qwen2 的全模态（视频 + 音频 + 文本）大模型，支持视频时序定位（temporal grounding）与多模态开放式问答。本文档只涵盖模型调用到结果预测的推理流程。 另外需要系统装有 ffmpeg（用于从视频提取音频）。 下载 eCityOmini checkpoint: https://huggingface.co/mxxxxxxxxxxxxxxxxx/ChronusOmni checkpoint 目录内需包含 LLM 权重、tokenizer、config 以及 BEATs 语音编码器权重（BEATsiter3plusAS2MfinetunedonAS2Mcpt2.pt）。视觉塔权重已包含在 LLM checkpoint 中，无需单独下载。 输入视频路径 + 问题，一条命令完成 ffmpeg 提取音频 → 均匀抽帧 + 时间戳 → 模型推理 → 打印结果，临时音频文件自动清理： 模型按 From second{X} to second{Y}. 回答，脚本解析后打印： 即 [start, end]，保留一位小数；解析失败时回退打印模型原始输出。 无外网服务器报错 couldn't connect to huggingface.co... openai/clip-vit-large-patch14 加载视觉塔时 chronus/model/multimodalencoder/oryxvit.py 会从 HuggingFace 下载 CLIP image processor 的配置文件（几 KB）。任选一种解决： 1. 运行前设置镜像：export…
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eCityAI-Sup
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