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801: Merged LLMs Are Smaller And More Capable, with Arcee AI's Mark McQuade and Charles Goddard
Super Data Science: ML & AI Podcast with Jon Krohn
Efficiency in Model Activation
Sparse upcycling is a technique that involves using a sparse model, in contrast to dense models like GPT-4. Dense models require all parameters to be activated for generating a response, leading to high computational requirements. In contrast, sparse models like llama three, 2, require the activation of only a smaller portion of parameters, making them more efficient in terms of computation.
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