Breaking the 1.58-bit Barrier: New Ternary LLM Storage Method Unveiled
Researchers have introduced a new storage method for Ternary Large Language Models (LLM) that breaks the 1.58-bit barrier, potentially leading to more efficient AI processing. The method, called BITCOS, takes into account the actual symbol distribution of ternary LLM models, which can store weights more compactly than existing methods. Lire la suite
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