#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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#BAT/USDT analysis :
#BAT is in an uptrend, consistently making new highs while trading above the 200 EMA. Currently, the price is above the support zone and is expected to bounce back from this level, resuming its bullish momentum to test previous highs.
TF : 1D
Entry : $0.2250
Target : $0.2943
SL : $0.2027
#BAT/USDT analysis :
#BAT is presently consolidating within a channel. The overall trend on the larger timeframes indicates a bearish outlook, suggesting a potential breakout from the channel to continue moving downwards towards lower price levels. It is advisable to wait for a breakout of the channel and a decline below the $0.1564 level for a short position entry.
TF : 2H
Entry : $0.1564
Target : $0.1313
SL : $0.1640
#BAT/USDT analysis -
#BAT is currently in downtrend, trading below the 200 EMA. The price is in a pullback phase and is projected to test the resistance zone close to the 200 EMA before potentially dropping further to revisit the previous lows. It is recommended to await the price to test the zone before considering a short entry.
TF : 4h
Entry : $0.1970
Target : $0.1728
SL : $0.2067