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What is Energy Efficiency in Neural Language Models about?
This study investigates the energy consumption and environmental impact of fine-tuning neural language models for text summarization tasks, specifically focusing on T5-base, BART-base, and LLaMA 3-8B. The research highlights the trade-offs between model performance and energy efficiency, emphasizing the need for sustainable practices in AI development. By quantifying the carbon footprint associated with these models, the authors advocate for the integration of environmental considerations into NLP technolog
- Author
- anvekarpranav
- Language
- EN