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Source channel @githubtrending · Post #14834 · Jun 17

#cuda DeepEP is a special communication library for Mixture-of-Experts (MoE) models. It helps these models work faster and more efficiently by improving how data is shared between different parts of the system. DeepEP supports low-precision operations and can handle data transfer between different types of connections, like NVLink and RDMA. This makes it very useful for both training and using AI models, especially when speed is important. Users benefit from faster processing times and better performance overall. https://github.com/deepseek-ai/DeepEP

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djangoproject

@djangoproject · Post #193 · 10/31/2016, 12:33 PM

http://deeplearning.net/software/theano/tutorial/index.html#basics In terms of #algorithm availability, you can get plenty of algorithms out of the box with scikit-learn. And if you want to customize every detail of your #models, #Python has #Theano. In addition, Theano is easily configured to run on the #GPU, which gives you a cheap and easy way to get much higher speeds without having to change a single line of code or delve into performance details.

djangoproject

@djangoproject · Post #352 · 06/25/2017, 08:57 AM

https://stxnext.com/blog/2017/04/12/most-popular-python-scientific-libraries/ The most popular Python scientific libraries: #Astropy #Biopython #Cubes #DEAP #SCOOP #PsychoPy #Pandas #Mlpy #matplotlib #NumPy #NetworkX #TomoPy #Theano #SymPy #SciPy #scikit_learn #scikit_image #ScientificPython #SageMath #Veusz #graph_tool #SunPy #Bokeh