corl-team/lime
Official implementation of the paper "You Do Not Fully Utilize Transformer's Representation Capacity"
This project offers a method to improve the performance of large language models (LLMs) during training by making their Transformer architectures more efficient. It takes an existing Transformer model and optimizes how its layers process information, resulting in faster convergence and better language understanding. AI/ML researchers and engineers working on developing or fine-tuning advanced language models would use this.
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Use this if you are a machine learning researcher or engineer aiming to enhance the training efficiency and performance of Transformer-based language models.
Not ideal if you are an end-user looking for a pre-trained language model or a tool for general data analysis, as this is a low-level optimization for model architecture.
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32
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Language
Python
License
Apache-2.0
Category
Last pushed
May 28, 2025
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