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Related Questions
- What are the key differences between model pruning and knowledge distillation, and how do they improve model efficiency?
- How does model quantization affect the performance of large language models, and what are the benefits of using low-precision arithmetic?
- Can you explain the concept of knowledge distillation and how it is used to transfer knowledge from a large language model to a smaller one?
- What are the trade-offs between model pruning, knowledge distillation, and quantization in terms of model performance and efficiency?
- How can model pruning be applied to large language models, and what are the challenges associated with it?
- What is the role of knowledge distillation in fine-tuning pre-trained language models, and how does it improve their performance?
- What are the benefits and limitations of using model quantization for large language models, and how does it impact model deployment in real-world applications?
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