Рет қаралды 853
in this video chris looks at how model providers are trending towards using grouped query attention vs traditional multi-headed attention in transformer models and how this is impacting output in areas such as summarization. in this video chris shows that you get better coherent output from models such as llama-2 or claude 3-opus over new models such as llama-3 or gemini or gemma. in the end, in certain scenarios such as summarization or generative content, gpt-4o still beats sonnet.
repo
github.com/chrishayuk/mha_gqa...