DeepSeek Sparse Attention From Scratch
Read OriginalThis article details a from-scratch implementation of DeepSeek Sparse Attention added to an LLMs-from-scratch repository. It describes how the mechanism replaces fixed sparse patterns with learned sparse patterns, using a lightweight indexer and selector to decide which prior tokens to attend to, rather than relying solely on a local window. The folder includes a README, a standalone GPT-style reference implementation, and tests. The article also references background concepts like regular causal attention and sliding-window attention for comparison.
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