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Data Science Machine Learning Data Analysis Books@DataScienceM P.1604
DATASCIENCEM Telegram 1604
4 advanced attention mechanisms you should know:

• Slim attention — 8× less memory, 5× faster generation by storing only K from KV pairs and recomputing V.

• XAttention — 13.5× speedup on long sequences via "looking" at the sum of values along diagonal lines in the attention matrix.

• Kolmogorov-Arnold Attention, KArAt — Adaptable attention with learnable activation functions using KANs instead of softmax.

• Multi-token attention (MTA) — 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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4 advanced attention mechanisms you should know:

• Slim attention — 8× less memory, 5× faster generation by storing only K from KV pairs and recomputing V.

• XAttention — 13.5× speedup on long sequences via "looking" at the sum of values along diagonal lines in the attention matrix.

• Kolmogorov-Arnold Attention, KArAt — Adaptable attention with learnable activation functions using KANs instead of softmax.

• Multi-token attention (MTA) — 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

https://www.tgoop.com/DataScienceM 🌟

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