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Source channel @githubtrending · Post #14827 · Jun 12

#typescript#desktop#docx#electron#html#languages#libreoffice#linux#macos#markdown#nodejs#office#offline#pandoc#pdf#productivity#windows#zettlr Zettlr is a free, open-source app that helps you write, organize, and publish your notes and documents using simple Markdown files. It works on Windows, macOS, and Linux, and lets you manage your notes with features like workspaces, tags, and powerful search, so you can quickly find what you need. Zettlr supports easy citations with reference managers like Zotero, offers code highlighting, dark mode, and flexible export options to PDF, Word, or LaTeX, making it ideal for students, researchers, and writers who want a privacy-focused, distraction-free way to work with their ideas and publish their work[1][3][5]. The benefit is that you can focus on your content, not formatting, and easily turn your notes into professional documents. https://github.com/Zettlr/Zettlr

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djangoproject

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

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