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Matthew Bermantoday +271AI Engineertoday +6The Builderstoday +1a16ztoday +220VC with Harry Stebbingsyesterday +383Jane Streetyesterday +119Y Combinatoryesterday +1硅谷1012 days agoPragerU3 days agoSemiAnalysis4 days ago

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TopicFine-tuningPersonMatthew Berman
5 slides12:03EN
Matthew Berman· Sep 6, 2024Reflection 70B: Self-Correction Claims and the Limits of a 2024 DemoMatthew Berman · Forward FutureMatthew Berman reviews a model trained to generate reflection steps. Its initial benchmark claims later proved difficult for independent evaluators to reproduce.AI HistoryFoundation ModelsEvals+2
2 slides6:28EN
Matthew Berman· Aug 29, 2023A Historical GPT-3.5 Fine-Tuning WalkthroughMatthew Berman · Forward FutureMatthew Berman demonstrates generating synthetic examples in Colab and training a model to use a distinctive tone.Fine-tuningSynthetic dataModels & training
2 slides8:49EN
Matthew Berman· Jul 19, 2023Llama 2’s 2023 Release: Model Sizes, License and SafetyMatthew Berman · Forward FutureMatthew Berman reviews Meta’s Llama 2 paper, its commercial license, model variants and safety evaluations.Open source & communityFoundation ModelsAI Alignment+1
4 slides11:42EN
Matthew Berman· May 31, 2023Guanaco and QLoRA: A 2023 Fine-Tuning and Model TestMatthew Berman · Forward FutureMatthew Berman reviews the QLoRA paper, explains the reported memory savings and tries Guanaco 65B on an informal prompt set.Fine-tuningQuantizationOpen-weight models+1
1:13:52EN
Matthew Berman· Apr 15, 2023Andriy Mulyar on GPT4All, Data Quality and Open Local ModelsMatthew Berman, Andriy Mulyar · Forward FutureThe Nomic AI co-founder explains how GPT4All emerged, why training data matters, and the tradeoffs between local and centralized AI.Local inferenceOpen-weight modelsData quality & curation+2