Sebastian Raschka, PhD
Artikel über Sebastian Raschka, PhD
Focusing on Post-Training
Why I'd invest in post-training existing open-weight LLMs, with Fireworks' Ember-1 as an example of more token-efficient reasoning.
MiMo-V2.6 Pro Architecture and Training Notes
Notes on MiMo-V2.6 Pro's GQA and sliding-window attention, agent training tasks, reward signals, and large RL batches.
It’s Easy to Dismiss Jev as Just a Classifier
A short note on Jev's generalization, possible encoder-style architecture and training, and Choice and Noul API examples.
Pacing != pacing development
My take on AI model pacing as a framework for release checks and the competitive pressure around model releases.
AI Reasoning Models Course on LinkedIn Learning
A 90-minute LinkedIn Learning course on how reasoning models relate to conventional LLMs and how they are developed.