{"id":10394,"date":"2023-12-14T13:05:23","date_gmt":"2023-12-14T16:05:23","guid":{"rendered":"https:\/\/4tuneagencia.digital\/blog\/microsoft-revela-modelo-de-linguagem-de-parametros-2-7b-phi-2\/"},"modified":"2023-12-14T13:05:23","modified_gmt":"2023-12-14T16:05:23","slug":"microsoft-revela-modelo-de-linguagem-de-parametros-2-7b-phi-2","status":"publish","type":"post","link":"https:\/\/4tuneagencia.digital\/blog\/microsoft-revela-modelo-de-linguagem-de-parametros-2-7b-phi-2\/","title":{"rendered":"Microsoft revela modelo de linguagem de par\u00e2metros 2.7B Phi-2"},"content":{"rendered":"
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Microsoft\u2019s 2.7 billion-parameter model Phi-2<\/a> showcases outstanding reasoning and language understanding capabilities, setting a new standard for performance among base language models with less than 13 billion parameters.<\/p>\n

Phi-2 builds upon the success of its predecessors, Phi-1 and Phi-1.5, by matching or surpassing models up to 25 times larger\u2014thanks to innovations in model scaling and training data curation.<\/p>\n

The compact size of Phi-2 makes it an ideal playground for researchers, facilitating exploration in mechanistic interpretability, safety improvements, and fine-tuning experimentation across various tasks.<\/p>\n

Phi-2\u2019s achievements are underpinned by two key aspects:<\/p>\n