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Source channel @TossLabChannel · Post #521 · 1月15日

#青龙更新 青龙 v2.18.1 更新说明 青龙 v2.18.1 发布!本次更新优化功能并修复问题: • 新增功能:内置 QLAPI 增加环境变量和系统通知 API。 • 调整:移除 nedb 和 sentry,不再支持 2.10.x 版本自动迁移。 • 修复:多语言翻译问题改进。 更新方法: • 面板更新:系统设置 -> 其他设置 -> 检查更新 • 容器内更新:执行 ql update • Debian 用户:直接同步更新。 • 宿主机更新:运行命令 docker run --rm -v /var/run/docker.sock:/var/run/docker.sock containrrr/watchtower -cR <容器名> 版本镜像: • 正式版:whyour/qinglong:latest • Python3.10 正式版:whyour/qinglong:python3.10 • Debian 版:whyour/qinglong:debian • Python3.10 Debian 版:whyour/qinglong:debian-python3.10 • NPM 安装:npm i -g @whyour/qinglong 📢 群聊: @TossLab 🎈 频道: @TossLabChannel ❗️ ❗️ ❗️ ❗️ ❗️ ❗️ ❗️ ❗️ 🔘折腾系列频道 - 全面介绍 🔘境外离岸银行教程合集目录 🔘折腾实验室优质Github项目合集

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@githubtrending · Post #15091 · 2025/08/24 11:30

#python#comfyui#diffusion#flux#genai#mlsys#quantization Nunchaku is a fast and efficient engine that runs 4-bit neural networks using a special method called SVDQuant, which compresses models to use less memory and speed up processing by 2 to 5 times compared to older methods. It supports advanced AI models for tasks like high-quality text-to-image generation and image editing, working best on modern NVIDIA GPUs. You can easily install and use it with ComfyUI, and it has active community support on Slack, Discord, and WeChat. This means you can generate or edit images quickly with less computing power, saving time and resources. It also offers tutorials and example workflows to help you get started smoothly. https://github.com/nunchaku-tech/ComfyUI-nunchaku

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@githubtrending · Post #15539 · 2026/03/05 11:30

#python#agent#llm#llm_agent#llm_reasoning#machine_learning_systems#mlsys#reinforcement_learning#rl AReaL is a free, open-source system for fast asynchronous reinforcement learning to train large AI models in math, coding, search, and agents. It decouples generation and training for up to 2.77x speedup, stable performance, and easy setup on single or 1000+ GPUs with algorithms like GRPO/PPO. Install via git/pip, run examples like GSM8K math instantly. You benefit by building top AI agents affordably and quickly, reproducing results with shared data/models, saving time/money vs. slow synchronous tools. https://github.com/inclusionAI/AReaL