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Source channel @githubtrending · Post #14819 · Jun 11
#jupyter_notebook MiniCPM is a family of highly efficient, open-source AI models designed to run well even on regular computers or mobile devices, not just powerful servers. The latest version, MiniCPM 4, is especially fast and smart, handling long texts and complex tasks much quicker than similar models, and it can be used for things like answering questions, writing summaries, and working with tools or data. MiniCPM also supports both English and Chinese, making it useful for bilingual users. The main benefit is that you get strong AI performance without needing expensive hardware, so it’s easy to use for many different applications[1][5]. https://github.com/OpenBMB/MiniCPM
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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.