Original): Ashish Abraham
Originally published in the direction of artificial intelligence.
No BS guide to build, train and refine the transformer architecture from scratch
Opeli recently introduced the very expected GPT-OSS models with an open people, a moment that invites a minute of reflection on how far we have come. Many years ago, even before Chatgpt, I remember that I read an article about the GPT model, probably GPT-2, which writes his own essays and poems, and they were only experiments. It quickly has become an integral part of my everyday life. It all began with a breakthrough publication “Attention all you need” in 2017 by Google Research. The architecture of the transformer was proposed, which soon supplied the first GPT-GPT-1 (generative pre-marked transformer) in 2018.
The article discusses the evolution of large language models (LLM) from the introduction of the transformer architecture to the latest achievements in open -level GPT models. It provides a comprehensive distribution of LLM construction and training using Pytorch, including various elements of the transformer framework, including tokenization, attention mechanisms and training strategies. The author emphasizes the importance of LLM refinement for specific tasks and the impact of these technologies on modern AI applications.
Read the full blog for free on the medium.
Published via AI
