Papers by Federico Lebron

1 papers
GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints (2023.emnlp-main)

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Challenge: Multi-query attention (MQA) can lead to quality degradation and training instability . it may not be feasible to train separate models optimized for quality and inference.
Approach: They propose a recipe for uptraining existing multi-head language model checkpoints into models with MQA using 5% of original training compute.
Outcome: The proposed model achieves comparable quality to multi-head attention with comparable speed.

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