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Source channel @githubtrending · Post #14659 · May 1
#cplusplus#arm#convolution#deep_learning#embedded_devices#llm#machine_learning#ml#mnn#transformer#vulkan#winograd_algorithm MNN is a lightweight and efficient deep learning framework that helps run AI models on mobile devices and other small devices. It supports many types of AI models and can handle tasks like image recognition and language processing quickly and locally on your device. This means you can use AI features without needing to send data to the cloud, which improves privacy and speed. MNN is used in many apps, including those from Alibaba, and supports various platforms like Android and iOS. It also helps reduce the size of AI models, making them faster and more efficient. https://github.com/alibaba/MNN
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@djangoproject · Post #316 · 04/28/2017, 06:09 AM
https://github.com/blissnd/easyxls Convert any #spreadsheet into a Python internal #dict/#array data structure, for easy processing. Can also handle pivot tables. For pivot table usage, header_row_start & header_col_start need to be set equal to the top left corner of the pivot table => header_row_start=8, header_col_start='c' in the included example. Column IDs must always be lowercase chars in quotes, e.g. 'a'.
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@djangoproject · Post #129 · 08/31/2016, 03:36 PM
https://pypi.python.org/pypi/numpy #NumPy is a general-purpose #array-processing package designed to efficiently manipulate large #multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional #arrays. NumPy is built on the #Numeric code base and adds features introduced by #numarray as well as an extended #C-API and the ability to create arrays of arbitrary type which also makes NumPy suitable for interfacing with general-purpose #data-base applications.