#language-modeling
#language-modeling

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Defining the Frontier: Multi-Token Prediction's Place in LLM Evolution | HackerNoon

Dong et al. (2019) and Tay et al. (2022) train on a mixture of denoising tasks with different attention masks (full, causal and prefix attention) to bridge the performance gap with next token pretraining on generative tasks.

Artificial intelligence

fromHackernoon

55 years ago

Multi-Token Prediction: Architecture for Memory-Efficient LLM Training | HackerNoon

Multi-token prediction enhances language modeling efficacy by allowing simultaneous forecasting of multiple tokens.

Improved model performance scales with increased size.

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#language-modeling#language-modeling

Defining the Frontier: Multi-Token Prediction's Place in LLM Evolution | HackerNoon

Multi-Token Prediction: Architecture for Memory-Efficient LLM Training | HackerNoon

#language-modeling
#language-modeling