#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
#FET/USDT Analysis-
The price has formed a symmetrical triangle pattern. Given the current bullish market scenario, there is a high probability of an upward breakout.
If the breakout occurs, the price is likely to rally toward the target zone from the breakout point.
T.F.- 1-D
ENTRY- as soon as it gives breakout
SL- 1.2
TARGET- 2.04
Note: If the stop-loss is triggered before entry, disregard the trade as the price action may develop differently.
#FET/USDT analysis :
#FET has broken down the 200 EMA and previous support levels. It is now undergoing a pullback and retesting the resistance zone. The price is expected to reject from there and bounce back to continue its bearish momentum.
TF : 1H
Entry : $1.170
Target : $1.057
SL : $1.252