#rust#app_launcher#desktop_application#dock#finder#multilanguage#seelen#seelen_ui#taskbar#tauri#tauri_app#tiling_window_manager#toolbar#tools#topbar#wallpaper#web#web_technologies#windows#windows_11
Seelen UI is a tool that helps you make your Windows desktop look and work better. You can change menus, widgets, and icons to make it look how you want. It also helps you work more efficiently with features like a Tiling Windows Manager, which arranges windows for easier multitasking. There's a media module for controlling music and an app launcher to quickly open apps. This makes your desktop more personalized and user-friendly, allowing you to work and enjoy your computer more effectively.
https://github.com/eythaann/Seelen-UI
#DL
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Zeus New Pytorch Ecosystem Tool
Zeus is an open source toolkit for measuring and optimizing power consumption of deep learning workloads.
🖥Github
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Main channel: @repo_science
Coupons: @freecoupons_reposcience
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#dl
Park, Chanwook, Sourav Saha, Jiachen Guo, Hantao Zhang, Xiaoyu Xie, Miguel A. Bessa, Dong Qian, et al. 2025. “Unifying Machine Learning and Interpolation Theory via Interpolating Neural Networks.” Nature Communications 16 (1): 1–12.
https://www.nature.com/articles/s41467-025-63790-8
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A few cool ideas in this model.
Introducing Gemma 3n: The developer guide - Google Developers Blog
https://developers.googleblog.com/en/introducing-gemma-3n-developer-guide/
#dl
There is this new lib called scale. One could compile CUDA code to use it on AMD GPU.
https://docs.scale-lang.com/manual/how-to-use/
I don't know who is more pissed off, NVidia or AMD.
#dl
This repo is really nice.
yuanchenyang/smalldiffusion: Simple and readable code for training and sampling from diffusion models
https://github.com/yuanchenyang/smalldiffusion
#dl
Google & USC benchmarked a prompt based forecasting method, and the results are amazing.
Cao D, Jia F, Arik SO, Pfister T, Zheng Y, Ye W, et al. TEMPO: Prompt-based Generative Pre-trained Transformer for time series forecasting. arXiv [cs.LG]. 2023. Available: http://arxiv.org/abs/2310.04948