ROIM1998/APT
[ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
This project helps machine learning engineers and researchers optimize large language models (LLMs) for specific tasks. It takes a pre-trained language model and a fine-tuning dataset as input, then outputs a more compact and efficient model that performs well on the target task. This is ideal for those who need to deploy LLMs with limited computational resources.
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Use this if you are a machine learning practitioner struggling with the high computational cost of fine-tuning and deploying large language models while aiming to maintain strong performance.
Not ideal if you are a casual user looking for an out-of-the-box, no-code solution for general text generation or analysis.
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Language
Python
License
MIT
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Last pushed
Jun 04, 2024
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