Openτensor Foundaτion (@opentensor): There's no point in doing decentralized training without efficient communication.
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There's no point in doing decentralized training without efficient communication. >> DiLoCo (H=15) ships ~480mb/merge with 163 syncs. >> SparseLoCo (H=15) ships ~5.5–17mb/merge at 0.78–3.12% density with 163 syncs Top-K Compression + 2 bit comms ~28–89× smaller per sync than DiLoCo. Subnet 3 :: @tplr If you have the algorithm, you can train large language models across disparate compute, collectively. "In the space of eight months or nine months, we've been able to scale our model from 1.2B to 70B, which represents 58x improvement" @DistStateAndMe Full E059 ft @const_reborn :: https://t.co/8QpHyIzF0D The holy grail of distributed AI training SN3 :: Templar :: @tplr_ai SN39 :: Basilica :: @basilic_ai SN81 :: Grail :: @grail_ai #SN3 #SN39 #SN81 #Bittensor