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Related Questions
- How do transformer-based language models handle long-range dependencies in text data?
- Can you explain the self-attention mechanism in transformer models and its impact on NLP tasks?
- What are the key differences between transformer-based models and recurrent neural networks (RNNs) in NLP?
- How do transformer-based language models handle out-of-vocabulary (OOV) words and unknown entities?
- What are some of the most common NLP applications that utilize transformer-based models, such as machine translation, text summarization, and question answering?
- How do transformer-based models leverage parallel processing and what are its benefits in NLP?
- Can you discuss the impact of pre-training and fine-tuning on the performance of transformer-based language models in NLP?
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