Inference scaling part 1.
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Inference scaling part 1. Starting with a modded text generation function (temperature scaling, top-p filtering, multinomial sampling) to generate diverse outputs for self-consistency and best-of-N (improving answer accuracy by>2x) 00:00 Introduction and recap 00:31 Training-time and inference-time scaling 07:52 What we'll implement 11:47 Notebook setup and model loading 17:43 Building a flexible text generation function 24:40 Chain-of-thought prompting 28:26 Sampling and output diversity 33:43 Next-token logits and greedy decoding 38:20 Temperature scaling step by step 42:46 Softmax and toke
Posted by Sebastian Raschka (508.9k followers) 2 h ago · 159 likes · 7.6k views · view the original post on X. Kept by the AI Radar as AI infra & evals.
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