#typescript#admin#admin_template#elegant#naive_ui#naive_ui_admin#pinia#typescript#unocss#vite6#vue#vue_admin#vue3
SoybeanAdmin is a modern, elegant, and powerful backend management template built with the latest technologies like Vue3, Vite6, TypeScript, Pinia, and UnoCSS. It offers a clear project structure, strict code standards, automated file routing, and built-in internationalization. It supports flexible permission routing, rich page components, and mobile-friendly layouts, making it ready to use without extra setup. This helps you quickly build or learn advanced admin systems with high code quality and customization options, saving time and improving development efficiency. It also provides command-line tools and mock data support for easier development and testing[1][4][5].
https://github.com/soybeanjs/soybean-admin
#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
#dl
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