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Source channel @githubtrending · Post #15298 · Nov 12

#python#android#android_emulator#google_apps#kernelsu#magisk#magiskonwsa#magiskonwsalocal#subsystem#windows#windows_10#windows_11#windows_subsystem_android#windows_subsystem_for_android#windows10#windowssubsystemforandroid#wsa#wsa_root#wsa_with_gapps_and_magisk#wsapatch Windows Subsystem for Android (WSA) support ended on March 5, 2025, and the Amazon Appstore was removed from the Microsoft Store, but you can still manually install and use WSA on Windows 10 or 11 via unofficial builds like WSABuilds from GitHub. These builds include options with Google Play Services and root access (Magisk). If you face issues with apps crashing or not starting after recent Windows updates, try using older or "NoGApps" builds as workarounds. Backing up your data before uninstalling or updating WSA is recommended. This lets you keep running Android apps on Windows despite official support ending. https://github.com/MustardChef/WSABuilds

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

#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 · 03/05/2026, 11:30 AM

#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