@eliebakouch
Wow, pretty cool that they also open sourced a FSDP2 compatible Muon and PolyNorm working with @huggingface kernels! https://t.co/Gqw7Hpj1v3
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"text": "Motif 2.6B tech report is pretty insane, first time i see a model with differential attention and polynorm trained at scale!\n\n> It's trained on 2.5T of token, with a \"data mixture schedule\" to continuously adjust the mixture over training.\n> They use WSD with a \"Simple moving average\" averaging the last 6 ckpt every 8B token.\n> They trained on Finemath, Fineweb2, DCLM, TxT360.\n> Lot of details in the finetuning data they used, for instance they used EvolKit and did some \"dataset fusion\" to have more compressed knowledge into the data.\n> They mention they also tried Normalized GPT, QK-Norm and Cross Layer Attention.",
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