
Dynamic Token Merging for Efficient Byte-level Language Models with Julie Kallini - #724
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Exploring Tokenization and Architecture Optimization in Machine Learning
This chapter delves into the advancements in tokenization and architecture optimization for machine learning. It highlights the shift towards aligning model architectures with specific use cases to create more efficient and tailored solutions beyond the traditional transformer models.
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