This AI Paper from China Proposes Continuity-Relativity indExing with gAussian Center (CREAM): A Easy but Efficient AI Methodology to Lengthen the Context of Massive Language Fashions
Massive language fashions (LLMs) like transformers are usually pre-trained with a set context window measurement, resembling 4K tokens. Nonetheless, many purposes require processing for much longer contexts, as much as 256K tokens. Extending the context size of those fashions poses challenges, significantly in guaranteeing environment friendly use of knowledge from the center a part of…