Summary:
- This article discusses a new metric called Effective State Size (ESS) that can be used to quantify the memory utilization of sequence models, such as language models and recurrent neural networks.
- ESS provides a way to measure the amount of information stored in the hidden states of these models, which is important for understanding their performance and optimizing their memory usage.
- By using ESS, researchers and developers can better understand the trade-offs between model size, memory usage, and performance, and make more informed decisions when designing and deploying these types of models.