#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
https://github.com/aio-libs/aiohttp-mako
#mako template renderer for #aiohttp.web based on aiohttp_jinja2. Library has almost same api and support python 3.5 (PEP492) syntax. It is used in aiohttp_debugtoolbar.
#Mako is a #template library written in Python. It provides a familiar, non-XML syntax which compiles into Python modules for maximum performance. Mako's syntax and #API borrows from the best ideas of many others, including #Django and #Jinja2 templates, #Cheetah, #Myghty, and #Genshi. Conceptually, Mako is an embedded Python (i.e. Python Server Page) language, which refines the familiar ideas of componentized layout and inheritance to produce one of the most straightforward and flexible models available, while also maintaining close ties to Python calling and scoping semantics.
http://www.makotemplates.org/