使用 Intel Sapphire Rapids 加速 PyTorch Transformers 模型 - 第一部分
Original: Accelerating PyTorch Transformers with Intel Sapphire Rapids - part 1
This article is the first installment in a collaboration series between Hugging Face and Intel, focusing on how to accelerate PyTorch…
Hugging Face 與 Intel 合作，展示如何在新一代 Intel Sapphire Rapids 處理器上加速 Transformer 模型。 透過內建的 Intel AMX（進階矩陣擴充）指令集，能顯著提升 BF16 與 INT8 的運算效率。 開發者只需搭配 optimum-intel 庫，即可輕鬆在 CPU 上實現高達數倍的推理與訓練加速，無需繁瑣的底層代碼修改。
This article is the first installment in a collaboration series between Hugging Face and Intel, focusing on how to accelerate PyTorch Transformer models using 4th Generation Intel Xeon Scalable Processors (codenamed Sapphire Rapids).
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