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Source channel @githubtrending · Post #14923 · Jul 7

#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

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Repositorio data science

@repo_science · Post #4131 · 05/18/2024, 09:06 PM

​​#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 -----

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Am Neumarkt 😱

@amneumarkt · Post #706 · 11/21/2025, 07:53 AM

#dl Introducing more symmetries in attention https://github.com/NVIDIA/torch-harmonics https://neurips.cc/virtual/2025/loc/san-diego/poster/117783

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@amneumarkt · Post #691 · 10/05/2025, 07:41 AM

#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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@amneumarkt · Post #683 · 06/28/2025, 07:04 AM

#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/

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@amneumarkt · Post #681 · 06/14/2025, 08:43 AM

#dl So tensorflow and jax are deprecated in the transformers package. https://github.com/huggingface/transformers/pull/38758

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@amneumarkt · Post #625 · 10/03/2024, 09:31 PM

#dl PyTorch Native Architecture Optimization: torchao | PyTorch https://pytorch.org/blog/pytorch-native-architecture-optimization/

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@amneumarkt · Post #602 · 07/20/2024, 05:48 AM

#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.

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@amneumarkt · Post #556 · 03/16/2024, 09:09 AM

#dl This repo is really nice. yuanchenyang/smalldiffusion: Simple and readable code for training and sampling from diffusion models https://github.com/yuanchenyang/smalldiffusion

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@amneumarkt · Post #506 · 11/13/2023, 08:30 AM

#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

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