txsun1997/awesome-early-exiting
A curated list of Early Exiting papers, benchmarks, and misc.
This resource helps machine learning practitioners find research papers and benchmarks related to 'Early Exiting' techniques, primarily in Natural Language Processing. It provides a curated list of research that shows how to make large language models predict results faster without losing accuracy. Data scientists or AI researchers focused on model optimization would use this to stay updated on efficiency improvements for deep learning models.
119 stars. No commits in the last 6 months.
Use this if you are working with large language models and need to find methods to significantly speed up their inference time for real-time applications or resource-constrained environments.
Not ideal if you are looking for ready-to-use code implementations or a general overview of machine learning optimization techniques beyond early exiting.
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MIT
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Last pushed
Oct 26, 2023
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