KEYPO and the small speculative

[prisilabr88]

Editing on the content generated by the small speculative model in a parallel processing manner. Finally, the most appropriate part is selected as the result from all the generated content. For example, if the user inputs model quickly generates big data key skills, then KEYPO big, KEYPO big data, KEYPO big data, KEYPO Big data gateway, KEYPO big data key, KEYPO big data key skills, KEYPO big data key skills are all handed over to large language models to predict the next word. If the large language model generates big, number, data, guan, key, technical,.

Energy, . respectively, you can find that the large language model predicts czech republic telegram number KEYPO big data key The next word is citation, which is different from the technique generated by the small speculative model, but the big data key is the same part of both the small speculative model and the large language model, so you can use the big data key as part of the final result and perform the above steps again. In this way, if the generated content of a small speculative model can be properly utilized, a large language model will have the opportunity to generate a.

Piece of content of the same quality in the time it takes to generate a single word, thereby greatly increasing the generation speed. Use a small speculative model SSM to pregenerate content and let a large language model run textbased Solitaire in parallel The newly upgraded KEYPO Big Data Key Engine in KEYPO Suite not only provides public opinion analysis services based on largescale language models, but is also supplemented by a variety of advanced AI artificial intelligence technologies to create the GPT Intelligent Reporting function , and accelerates the generation time from more than a minute to just tens.