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* imp compaction * fix lint * cassette gen * cassette gen * improve assert * adding azure * fix global docstring
104 lines
5.4 KiB
YAML
104 lines
5.4 KiB
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in large language models. Focus on architecture improvements and training techniques.\n\n[ASSISTANT]:
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I''ll research the latest developments in large language models. Based on my
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knowledge, recent advances include:\n1. Mixture of Experts (MoE) architectures\n2.
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you go deeper on the MoE architectures? What are the key papers?\n\n[ASSISTANT]:
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Key papers on Mixture of Experts:\n- Switch Transformers (Google, 2021) - simplified
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MoE routing\n- GShard - scaling to 600B parameters\n- Mixtral (Mistral AI) -
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open-source MoE model\nThe main advantage is computational efficiency: only
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a subset of experts is activated per token.\n</conversation>\n\nCreate a summary
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