#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
Visionaries, it's time to expand our horizons & explore another new platform together!! 🤜🤛
Join us on #Threads for exclusive content, engaging discussions, and endless opportunities to WIN! 🔝
Show us your love on #Threads too!
@vision11official
Please follow for latest update👇👇
https://www.threads.net/@vision11official
Threads – twitter dasturiga o’xshash bo'lgan dastur bo'lib, faqat Instagramning matnga asoslangan versiyasi hisoblanadi.
ℹ️ Bu dastur instagram bilan bog'langan va siz dasturdan foydalanishingiz uchun instagram akkaunt talab qilinadi.
😎Threadsni o'rnatganlar bo'lsa kompyuter bilimlari kanalimiz sahifasiga obuna bo'ling – http://threads.net/@kompyuter_bilimlari
😄 Rasmga baxo berish esdan chiqmasin-aa))
👉🏼Birinchi raqamli Windows Blog | #threads / #atama
Сколько времени вы проводите в соцсетях?🧐
Кажется, скоро будем проводить еще больше, ведь в июле появилась новая сеть #Threads, которую все называют аналогом #Twitter.
💼Некоторые бренды уже начали использовать новый инструмент в работе. Оставляйте комментарии, мы соберем подборку ваших мнений в наш канал в Дзене.
Как вы оцениваете запуск новой социальной сети Threads? Будете ли использовать в работе? И как?
Meta 旗下社交媒体 Threads 移动端日活超越 X 平台,网页端差距悬殊揭示社媒格局新变化
Similarweb报告显示,Threads移动端日活达1.415亿,已超越X平台。Threads的增长得益于Meta的交叉推广与功能完善;而X平台受AI争议及监管调查影响,美国日活大幅下滑。尽管X在网页端仍具绝对优势,但其领先地位正被削弱,Threads正逐渐成为主流社交工具。
标签:#threads#x
Created by RocM
官方频道:@rocCHL
官方群组:@roctech
官方合作:@rocmmbot