Paper : https://arxiv.org/abs/2404.14047
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Llama 3 degrades much more than Llama 2 when quantized. 🤔
📌 Most possible reason because Llama 3, trained on a record 15T tokens, captures extremely nuanced data relationships, utilizing even the minutest decimals in BF16 precision fully. Making it more sensitive to quantization degradation.
📌 So sensitive that even the smallest decimal points of each parameter offered by BF16 precision were filled and had a purpose. Other LLMs were trained for far less (2T), and thus did not have time to saturate smaller precision ranges of the parameters like Llama-3 did, and thus are not affected by quantization as much.
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