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Source channel @githubtrending · Post #15096 · Aug 26

#lua#layout#lua#neovim#neovim_plugin#neovim_ui#nvim#plugin#scratchpad#ui#ux#zen_mode#zenmode The no-neck-pain.nvim plugin for Neovim centers your active editing window by adding empty buffers on each side, creating padding that keeps your focus in the middle of the screen. It works right away without setup, supports multiple tabs, split windows, and integrates with popular file tree and dashboard plugins. You can customize its width, colors, and behavior, and even use the side buffers as scratchpads for notes. This helps reduce neck strain and improves focus, especially on wide monitors, by keeping your code or text centered and easy to read without distractions. https://github.com/shortcuts/no-neck-pain.nvim

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#lua #layout #neovim #neovim_plugin #neovim_ui #nvim #plugin #scratchpad #ui #ux #zen_mode #zenmode

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djangoproject

@djangoproject · Post #274 · 03/18/2017, 01:48 AM

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https://github.com/riga/tfdeploy Google's TensorFlow framework is taking off big-time now that it's at a full 1.0 release. One common question about it: How can I make use of the models I train in TensorFlow without using TensorFlow itself? #Tfdeploy is a partial answer to that question. It exports a trained TensorFlow model to "a simple #NumPy-based callable," meaning the model can be used in Python with Tfdeploy and the the NumPy math-and-stats library as the only dependencies. Most of the operations you can perform in TensorFlow can also be performed in Tfdeploy, and you can extend the behaviors of the library by way of standard Python metaphors (such as overloading a class). Now the bad news: Tfdeploy doesn't support GPU acceleration, if only because NumPy doesn't do that. Tfdeploy's creator suggests using the gNumPy project as a possible replacement. #Machine_learning

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