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Lila Sciences and Anyscale scale GLM-5.3-Flash to 1M token context

By PulseAugur Editorial · [1 sources] ·

Lila Sciences and Anyscale have successfully trained the open-source GLM-5.3-Flash model to handle sequences of 1 million tokens. This significant increase in context length was achieved by optimizing the training stack, including modifications to attention mechanisms and memory management, utilizing 64 B200 GPUs. The research, detailed in Anyscale's blog, highlights the importance of training on full-length scientific data and has contributed fixes upstream to Megatron-LM. AI

IMPACT Enables training on longer scientific datasets, potentially improving AI's ability to understand complex biological and experimental data.

RANK_REASON Research paper detailing a technical achievement in scaling model context length. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Anyscale blog →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Lila Sciences and Anyscale scale GLM-5.3-Flash to 1M token context

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4 / 100
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Research paper detailing a technical achievement in scaling model context length. [lever_c_demoted from research: ic=1 ai=1.0]
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model release, infra
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High
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Same-day
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COVERAGE [1]

  1. Anyscale blog TIER_1 English(EN) ·

    How Lila Sciences and Anyscale Scaled GLM-5.3-Flash Training to 1M tokens

    Dive into how Lila Science used an open stack to scale GLM-5.3-Flash training to 1 million tokens per sequence using SkyRL on Anyscale running 64 B200 GPUs

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