#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
#COTI/USDT analysis :
#COTI is currently forming higher highs (HHs) and higher lows (HLs) along the trendline. The price is consolidating above this trendline, suggesting a potential bounce back and a test of higher levels.
TF : 1W
Entry : $0.10200
Target : $0.18200
SL : $0.07670
#COTI/USDT analysis :
#COTI is in an uptrend, forming a structure of higher highs (HHs) and higher lows (HLs). The price has broken out and successfully retested the trendline, continuing its bullish trajectory. Currently, the price is trading above a minor resistance zone, which has now become a buy zone. It is anticipated that the price will rise further and test higher levels.
TF : 1H
Entry : $0.14450
Target : $0.16145
SL : $0.13292