flash-linear-attention and ring-sliding-window-attention
About flash-linear-attention
fla-org/flash-linear-attention
🚀 Efficient implementations of state-of-the-art linear attention models
This project offers highly optimized building blocks for developing next-generation AI models that can process very long sequences of information efficiently. It provides ready-to-use implementations of advanced 'linear attention' and 'state space' model architectures. AI researchers and machine learning engineers can use these components to create more powerful and scalable models for tasks like natural language understanding or time-series prediction.
About ring-sliding-window-attention
XunhaoLai/ring-sliding-window-attention
Ring sliding window attention implementation with flash attention
This is a specialized tool for machine learning engineers working on large language models. It helps train models more efficiently on very long text sequences by distributing the attention mechanism across multiple GPUs. You input the model's query, key, and value tensors, and it outputs the attention results, enabling faster training for long contexts.
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