Chinese scholars have proposed a new large model window extension method called SelfExtended (SE), which can triple the window length of large models with only four lines of code. This breakthrough technology is “plug and play” compatible with a variety of large models and has been proven on Mistral and Llama2 models. Through the SE method, the performance of large models in processing long text tasks has been significantly improved, effectively solving the coding overlimit problem faced by large models when processing long texts. This provides new directions and possibilities for large models to handle complex long text tasks.
Chinese scholars have released a new large model window extension method, SelfExtended (SE for short), which can triple the window length of large models with just four lines of code. SE is a "plug and play" method that can adapt to any large model, and has been successfully tested on Mistral and Llama2. After using SE processing, the model's performance in long text tasks is significantly enhanced. SE uses two attention mechanisms to solve the coding overlimit problem encountered by large models when processing long texts.
The emergence of the SelfExtended (SE) method provides a simple and efficient solution to the problem of long text processing in large models. Its "plug and play" feature also makes it easy to apply to various large models, demonstrating its powerful practicality. sex and broad application prospects. In the future, further improvement and perfection of SE methods will bring more possibilities to the development of large model technology.