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Rohan Pandey
@khoomeik
descending cross-entropy to ascend entropy @PeriodicLabs || prev research @OpenAI @CarnegieMellon '23
参加 February 2020
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Another Neon infra tidbit: @periodiclabs accelerated checkpoint conversion ~30x down to just 1 minute, helping us deploy faster to get rapid feedback from our labs. Our models train in Megatron, but SGLang inference consumes weights in HuggingFace format. Traditionally, conversion ran serially: 1. rebuild the entire checkpoint from individual weight tensors 2. convert the checkpoint 3. reshard it to be inference-ready This could take 30 min for a trillion parameter model! Noticing that conversion shouldn't require materializing the full checkpoint, @hsu_byron introduced Fast Resharding: 1. parallelize conversion across Ray actors 2. convert expert chunks directly instead of assembling the full expert tensor in memory We upstreamed Fast Resharding to Miles in PR #1371#. Now even you can deploy trained models to production in a matter of minutes.
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