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4 advanced attention mechanisms you should know:

β€’ Slim attention β€” 8Γ— less memory, 5Γ— faster generation by storing only K from KV pairs and recomputing V.

β€’ XAttention β€” 13.5Γ— speedup on long sequences via "looking" at the sum of values along diagonal lines in the attention matrix.

β€’ Kolmogorov-Arnold Attention, KArAt β€” Adaptable attention with learnable activation functions using KANs instead of softmax.

β€’ Multi-token attention (MTA) β€” Lets the model consider groups of nearby words together for smarter long-context handling.

Read the overview of them in our free article on
https://huggingface.co/blog/Kseniase/attentions

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100 Important Data Science Interview Questions.pdf
11.7 MB
πŸ“– 100 Essential Data Science Interview Questions

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