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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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Interesting Planet 🌍

@interesting_planet_facts · Post #1053 · 11/19/2025, 06:11 PM

🌎 In 1977, the Soviet Venera 14 probe recorded mysterious low-frequency “thunder”-like sounds on Venus. Scientists now attribute these to seismic activity or wind interacting with the planet’s dense atmosphere. Venus’s surface winds move slowly, but thick air carries sound much farther than on Earth. ✨ #Venus⚡#sounds⚡#space 👉subscribe Interesting Planet 👉more Channels ​

djangoproject

@djangoproject · Post #255 · 02/02/2017, 06:57 PM

https://github.com/tyiannak/pyAudioAnalysis #pyAudioAnalysis is a Python library covering a wide range of audio analysis tasks. Through pyAudioAnalysis you can: Extract #audio features and representations (e.g. mfccs, spectrogram, chromagram) Classify unknown #sounds Train, parameter tune and evaluate classifiers of audio segments Detect audio events and exclude silence periods from long recordings Perform supervised segmentation (joint segmentation - classification) Perform unsupervised segmentation (e.g. speaker diarization) Extract audio thumbnails Train and use audio regression models (example application: emotion recognition) Apply dimensionality reduction to visualize audio data and content similarities