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Source channel @githubtrending · Post #15526 · Feb 27

#python#ai#ai_agent#ai_infra#kubernetes#sandbox OpenSandbox is a general-purpose sandbox platform that lets you safely run AI applications, code, and agents in isolated environments. It provides multi-language SDKs for Python, Java, and JavaScript, making it easy to integrate into your projects. The platform supports Docker and Kubernetes runtimes, so you can run sandboxes locally or at scale. Key benefits include running code generated by AI models safely, executing data analysis, automating browser tasks, and training AI systems without risking your main system. Whether you're building coding agents, testing applications, or letting AI handle complex tasks, OpenSandbox gives you a secure, controlled space to experiment and execute code without side effects. https://github.com/alibaba/OpenSandbox

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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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