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Related Questions
- What are the typical energy consumption patterns of large language models during training and inference stages?
- How do different model architectures and hyperparameters impact energy consumption and carbon footprint?
- Can you provide a breakdown of the energy consumption and carbon footprint of transformer-based models versus other architectures?
- What are the primary factors contributing to energy consumption during model training, and how can they be optimized?
- How does inference energy consumption vary across different model sizes and input lengths?
- Can you estimate the carbon footprint of training and deploying a large language model, including data preprocessing and storage?
- What are some strategies for reducing energy consumption and carbon footprint in large language model training and inference pipelines?
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