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Source channel @githubtrending · Post #14747 · May 25

#python#deep_learning#intel#machine_learning#neural_network#pytorch#quantization Intel Extension for PyTorch boosts the speed of PyTorch on Intel hardware, including both CPUs and GPUs, by using special features like AVX-512, AMX, and XMX for faster calculations[5][2][4]. It supports many popular large language models (LLMs) such as Llama, Qwen, Phi, and DeepSeek, offering optimizations for different data types and easy GPU acceleration. This means you can run advanced AI models much faster and more efficiently on your Intel computer, with simple setup and support for both ready-made and custom models. https://github.com/intel/intel-extension-for-pytorch

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djangoproject

@djangoproject · Post #154 · 09/04/2016, 12:14 PM

https://docs.python.org/2/library/modulefinder.html This #module provides a #ModuleFinder class that can be used to determine the set of modules imported by a script. modulefinder.py can also be run as a script, giving the filename of a Python script as its argument, after which a report of the imported modules will be printed.

djangoproject

@djangoproject · Post #145 · 09/02/2016, 03:28 AM

https://docs.python.org/3/library/modulefinder.html This module provides a #ModuleFinder class that can be used to determine the set of #modules#imported by a #script. modulefinder.py can also be run as a script, giving the #filename of a Python script as its argument, after which a report of the imported modules will be printed.