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首先,Both models use sparse expert feedforward layers with 128 experts, but differ in expert capacity and routing configuration. This allows the larger model to scale to higher total parameters while keeping active compute bounded.,推荐阅读WhatsApp网页版获取更多信息
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第三,Both of the vector sets are stored on disk in .npy format (simple format for storing numpy arrays
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最后,These optimizations yield significantly higher tokens per second per GPU at the same latency targets, enabling higher user concurrency and lower infrastructure costs.
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