Sebastian Raschka, PhD

Why I'd invest in post-training existing open-weight LLMs, with Fireworks' Ember-1 as an example of more token-efficient reasoning.

Notes on MiMo-V2.6 Pro’s GQA and sliding-window attention, agent training tasks, reward signals, and large RL batches.

A short note on Jev's generalization, possible encoder-style architecture and training, and Choice and Noul API examples.

Music mood classification project: predicting a song's emotional valence from lyrics with NLP, feature engineering, and scikit-learn in Python.

This has really been quite a journey for me lately. And regarding the frequently asked question “Why did you choose Python for Machine Learning?” I guess it...