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Sebastian Raschka

@rasbt
ML/AI research engineer. Ex stats professor. Author of "Build a Large Language Model From Scratch" (amzn.to/4fqvn0D) & reasoning (mng.bz/lZ5B)
United States
sebastianraschka.com
Joined October 2012
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  • Pinned
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    Sebastian Raschka
    @rasbt
    Jul 18
    How can an LLM switch between low-, medium-, and high-effort reasoning? And how does an LLM learn to reason more or less? I put together a “little” article explaining how these effort levels are implemented at inference time and during training.
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    Sebastian Raschka
    @rasbt
    Aug 15
    A short illustration of how the Claude's watermarking is supposed to work (based on my read of their released materials). In general, when we are generating tokens, there can be multiple high-scoring tokens at certain next-word positions. Usually, we sample with top-k or top-p
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    Anthropic
    @AnthropicAI
    Aug 14
    We’ve written an FAQ to answer some of the questions we've received about watermarking. In summary: • We’re implementing watermarking to comply with the EU AI Act. Other major model developers have signed the same Code of Practice and will also be implementing watermarking;
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    Sebastian Raschka
    @rasbt
    Aug 12
    Build a Reasoning Model (From Scratch) is now finally also available on Amazon! Thanks so much to everyone who preordered! One important note for readers in India: please avoid ordering through @amazon India (@amazonIN) for now since they are selling counterfeit black-and-white
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    Sebastian Raschka
    @rasbt
    Aug 11
    Whoa, Meta released a new open-weight LLM yesterday, something that hasn't happened since the good old Llama days. Their Meta Muse Glimmer model is a 30B multimodal reasoning model with a Gemma-like architecture design. (“Glimmer” is probably a wordplay on “Spark,” the more
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    Sebastian Raschka
    @rasbt
    Aug 7
    Just saw that the LLMs-from-scratch repository passed 100,000 stars on GitHub! This is super cool and motivating. I am really happy to see that this open-source repo has helped so many people. Thanks also to everyone who shared ideas and opened PRs with improvements! Of course,
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