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Source channel @githubtrending · Post #15141 · Sep 13

#python#large_language_models#machine_learning_systems#natural_language_processing Flash Linear Attention (FLA) is a fast, memory-efficient library for advanced linear attention models used in transformers, written in PyTorch and Triton, and compatible with NVIDIA, AMD, and Intel GPUs. It offers many state-of-the-art linear attention models and fused modules that speed up training and reduce memory use. You can easily replace standard attention layers in your models with FLA’s efficient versions, improving training and inference speed, especially for long sequences. FLA supports hybrid models mixing linear and standard attention, and integrates with Hugging Face Transformers for easy use and evaluation. This helps you train and run large language models faster and with less memory, making your AI projects more efficient and scalable. https://github.com/fla-org/flash-linear-attention

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Crypto M - Crypto News

@CryptoM · Post #65351 · 04/13/2026, 01:57 AM

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🚀 Barclays Analysts: Asian Central Banks Likely to Maintain Monetary Policy Amid Middle East Conflict On April 13, Barclays Bank's fixed income, foreign exchange, and commodities research team released a report suggesting that Asian central banks may keep their monetary policies unchanged in the short term due to ongoing Middle East conflicts. According to Jin10, the analysts noted that the Monetary Authority of Singapore is likely to maintain its current policy this week, expressing concerns over the risks of extreme negative growth rather than inflation. Meanwhile, Barclays believes that unless the U.S. dollar significantly depreciates against the Indonesian rupiah before the upcoming Bank Indonesia meeting, the Indonesian central bank is unlikely to quickly resume its rate-cutting cycle. Additionally, the central banks of Thailand and the Philippines, which are also holding meetings this month, are expected to remain on hold. #Barclays#AsianCentralBanks#MonetaryPolicy#MiddleEastConflict#Singapore#Indonesia#Thailand#Philippines#InterestRates#BankIndonesia#USdollar#Rupiah#RateCut

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