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State of the Art: Training >70B LLMs on 10,000 H100 clusters

Imbue and Databricks have released extensive details about their LLM training infrastructure and methodologies. Imbue's internal model, which reportedly surpasses GPT-4o on certain benchmarks, was trained using significantly less data than Llama 3 70B. The companies are sharing infrastructure scripts, a cost-aware hyperparameter optimizer named CARBS, and cleaned benchmark datasets to aid the broader AI community in training large language models. This release offers unprecedented educational insight into the hardware and ML intricacies involved in large-scale LLM development. AI

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RANK_REASON Release of detailed infrastructure, benchmarks, and training methodologies for LLMs, including an internal model that outperforms GPT-4o on specific tasks.

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State of the Art: Training >70B LLMs on 10,000 H100 clusters

COVERAGE [1]

  1. Latent Space Podcast TIER_1 · Josh Albrecht and Jon Frankle ·

    State of the Art: Training >70B LLMs on 10,000 H100 clusters

    <p><strong>It’s return guest season here at Latent Space!</strong> We last talked to <a href="https://www.latent.space/p/imbue" target="_blank"><strong>Kanjun in October</strong></a> and <a href="https://www.latent.space/p/mosaic-mpt-7b" target="_blank"><strong>Jonathan in May</s…