#rust#ai_agent#developer_tools#enterprise#fine_tuning#on_prem#open_source#rag#self_hosted#swe_bench#vscode
Refact.ai is a free, open-source AI software development agent that helps you code faster and smarter by deeply understanding your code and integrating with tools like GitHub, databases, Docker, and debuggers. It offers unlimited, context-aware code auto-completion, can generate, refactor, explain, debug code, and create tests and documentation across 25+ programming languages. You can run it securely on your own servers, use top AI models like GPT-4o, and connect your own API keys. This means you save time on repetitive tasks, improve code quality, and collaborate better, making your development workflow much more efficient and productive[1][3][5].
https://github.com/smallcloudai/refact
#DL
📱
Zeus New Pytorch Ecosystem Tool
Zeus is an open source toolkit for measuring and optimizing power consumption of deep learning workloads.
🖥Github
-----
Main channel: @repo_science
Coupons: @freecoupons_reposcience
-----
#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