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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 #64665 · 04/09/2026, 01:15 PM

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🚀 Gibbs Mura Investigates Drift Protocol Theft in Class Action Gibbs Mura, a U.S. law firm, has announced a class action investigation into the theft involving Drift Protocol, with the funds involved estimated between $280 million and $285 million. According to ChainCatcher, over $230 million in USDC was transferred to Ethereum via Circle's Cross-Chain Transfer Protocol (CCTP). Gibbs Mura argues that although Circle has the technical capability to freeze funds, it did not take such action during the attack. The firm is currently assessing whether investors can claim against Circle for 'failure to intervene timely,' 'insufficient monitoring,' and 'not fulfilling stablecoin responsibilities.' Affected users are encouraged to join the lawsuit to aid in the recovery of funds. #GibbsMura#DriftProtocol#ClassAction#TheftInvestigation#USDC#Ethereum#Circle#CrossChainTransfer#StablecoinResponsibilities#FundsRecovery

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