#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
#BAKE/USDT analysis :
#BAKE is currently retracing towards the 200 EMA. The price is expected to retest this moving average before continuing its bearish momentum. The current level presents a favorable opportunity for a long entry.
TF : 2h
Entry : $0.1507
Target : $0.1700
SL : $0.1414
#BAKE/USDT analysis :
The price is in an uptrend, forming higher highs (HHs) and higher lows (HLs) above the 200-period exponential moving average (200 EMA). The price is expected to bounce back from this level and continue its bullish momentum, aiming to test the previous swing high.
TF : 1h
Entry : $0.2783
Target : $0.2929
SL : $0.2705