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Source channel @githubtrending · Post #15264 · Nov 3

#shell You can run Firefox inside a Docker container that lets you access its graphical interface through a web browser or VNC client without installing Firefox on your computer. This container stores your settings and data persistently, supports customization via environment variables, and can be secured with encrypted connections and password protection. It also allows audio streaming and file management through the browser. Using this container simplifies deployment, keeps Firefox isolated for security, and makes it easy to update or move between systems while preserving your data and preferences. This setup benefits you by providing a portable, secure, and easy-to-manage Firefox experience. https://github.com/jlesage/docker-firefox

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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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