Meta AI 發佈 MobileLLM-R1：輕量級邊緣推理模型，參數不足 10 億，性能提升顯著
Meta AI 近日推出了 MobileLLM-R1，這是一系列輕量級邊緣推理模型，目前已在 Hugging Face 上發佈。該系列模型參數範圍從140M 到950M，專注於高效的數學、編碼和科學推理，且在不足10億的參數規模下實現了優秀的性能表現。MobileLLM-R1的最大模型爲 MobileLLM-R1-950M，採用了一系列架構優化設計:包括22層 Transformer 結構、24個注意力頭和6個分組 KV 頭。模型的嵌入維度爲1536，隱藏層維度爲6144。此外，模型還採用了分組查詢注意力（GQA）來減少計算和內存需求，塊級權重共享技術降低了參數數量而不顯著
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