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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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@abmedia_news · Post #24587 · 05/14/2026, 03:02 AM
【📜 政策監理｜Bitget執行長Gracy Chen發表看法，清晰法案會改變誰的命運？】 #CLARITYAct#加密貨幣監管#GracyChen Bitget執行長Gracy Chen於5月14日指出，CLARITY Act是產業成熟的轉折。 法案H.R. 3633要求落實資產隔離，並以聯邦規則取代碎片化MTL規範。此舉將獎勵合規先鋒，並淘汰披著DeFi外衣、挪用資產的模式。 📍閱讀全文： https://abmedia.io/bitget-ceo-on-clarity-act 📍 訂閱鏈新聞頻道：https://linktr.ee/abmedia.io
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@venturevillagewall · Post #3891 · 01/16/2025, 10:00 AM
AI Tokens Soar in Market Value Total market cap for AI-related tokens is projected to reach $60 billion by 2025, according to Bitget CEO Gracy Chen. Initial applications of neural networks will likely include trading and crypto wallet management, with exchanges launching their own agents to enhance customer service. CoinGecko’s 2024 crypto industry report shows AI agent tokens surged 322% in Q4, rising in market cap from $4.8 billion to $15.5 billion. Industry experts foresee a transformation in the Web3 sector thanks to AI-based assistants. Read more details on ForkLog #AI#Crypto#VC#Web3#Trading#Investment#Tokens#MarketCap#CoinGecko#NeuralNetworks#CustomerService#Blockchain#AIAgents#Q4Growth#CryptoReport#Bitget#GracyChen#Web3Transformation#HindenburgResearch#Decacorn#ColossalBiosciences