Niels Rogge(@NielsRogge):For folks wondering what Sliding Window Attention is, there's a method for it on Papers with Code Sliding Window Attention (SWA): A local attention pattern that restricts each token to attending only within a fixed-size neighborhood instead of the full sequence. This reduces attention and KV-cache memory for long-context models, while periodic global-attention layers can preserve broader context. Find it here:

Niels Rogge

@NielsRogge

ML Engineer @huggingface. Building @KU_Leuven grad. General interest in machine & deep learning. Making AI more accessible for everyone!

参加 April 2010

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Niels Rogge@NielsRogge

2026.08.31 15:05

For folks wondering what Sliding Window Attention is, there's a method for it on Papers with Code Sliding Window Attention (SWA): A local attention pattern that restricts each token to attending only within a fixed-size neighborhood instead of the full sequence. This reduces attention and KV-cache memory for long-context models, while periodic global-attention layers can preserve broader context. Find it here: