Attention Wasn't All We Needed
SMRTR summary
Transformer models have evolved with advanced techniques to improve efficiency and performance. Key developments include Group Query Attention for reduced memory usage, Multi-head Latent Attention for handling long sequences, and Flash Attention for optimized memory access. These innovations enable faster training, inference on longer inputs, and better scalability for large language models.
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