Sebastian Raschka Releases Inference Scaling Tutorial: Self-Consistency Boosts Accuracy Over 2x
rasbt · x · 2026-09-19
LLM researcher Sebastian Raschka (rasbt) released part 1 of his inference scaling video series on YouTube, complete with notebooks.
The tutorial starts by distinguishing training-time from inference-time scaling, then walks through modifying a text generation function—implementing temperature scaling, top-p filtering, and multinomial sampling—to generate diverse outputs for self-consistency and best-of-N decoding. Raschka notes this improves answer accuracy by more than 2x.
Chapters cover the scaling concepts (00:31), what will be implemented (07:52), notebook setup and model loading (11:52), and building a flexible generation function (17:43 onward). Ideal for anyone who wants to understand sampling and voting-based decoding from first principles.
Related event: rasbt Releases Inference Scaling Tutorial Video(2 posts)→
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