Upstage AI has recently made a major breakthrough, and its deep expansion method (DUS) has demonstrated excellent performance on the SOLAR10.7B large model. By cleverly splicing two 7B Alpaca models, DUS goes beyond traditional model extension methods while efficiently integrating infrastructure. This method is based on the Mistral7B substrate, and the basic model and fine-tuned model have been open sourced for the convenience of developers and researchers. User feedback has also confirmed the excellent performance of DUS in practical applications, bringing new development directions and possibilities to the field of deep learning.
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Recently, the deep expansion method (DUS) proposed by Upstage AI has achieved impressive results on the SOLAR10.7B large model. It innovatively spliced two 7B alpacas to efficiently integrate infrastructure. In terms of technical implementation, Mistral7B was selected as the base material, successfully surpassing the traditional expansion method, and open sourced the basic model and fine-tuning model. User feedback shows that this technology performs superiorly in actual data processing, bringing new possibilities to the field of deep learning.
Upstage AI's DUS method, with its high efficiency and open source, provides new ideas for the expansion and application of large models. Its superior performance and wide applicability herald a new chapter in the future development of the deep learning field. We look forward to more DUS-based applications and research results appearing in the future.