AI 模型乱码解决方法 - 编码配置和字符集修复

显存不足的解决方法，AI模型内存优化技巧。提供模型量化、批处理调整、内存清理等多种方法，帮助用户在有限显存条件下运行AI模型。

Solutions for insufficient VRAM, AI model memory optimization techniques. Provides multiple methods such as model quantization, batch adjustment, memory cleaning, helping users run AI models under limited VRAM conditions.

AI环境依赖缺失的排查步骤，提供完整检查清单。按步骤检查Python版本、库文件、环境变量等，快速定位并解决依赖缺失问题，确保AI环境完整。

Troubleshooting steps for missing AI environment dependencies, providing a complete checklist. Checks Python version, library files, environment variables step by step, quickly identifying and resolving dependency missing issues, ensuring complete AI environment.

端口占用导致AI服务启动失败的解决方案详解。介绍如何检查端口占用情况、终止占用进程、修改默认端口等方法，确保AI服务正常启动和运行。

Detailed solutions for AI service startup failure due to port occupation. Introduces how to check port occupation status, terminate occupying processes, modify default ports and other methods, ensuring normal startup and operation of AI services.