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Related Questions
- What are some common techniques for model pruning to reduce the size of a large language model?
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- What are some strategies for quantizing model weights and activations to reduce memory usage?
- How can knowledge distillation be used to transfer knowledge from a large teacher model to a smaller student model?
- What are some techniques for reducing the number of parameters in a model, such as weight sharing or sparse representations?
- How can model architecture modifications, such as depth and width reduction, be used to reduce model size?
- What are some strategies for using transfer learning to leverage pre-trained models and reduce the need for large-scale training?
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