Seq2Seq Models: Decoding the Future of Text Transformation!
Analysis
Key Takeaways
- •Seq2Seq models are a fundamental architecture for transforming text data in NLP.
- •They are used in important tasks like machine translation and text summarization.
- •The article explores the core concepts of Encoder-Decoder structure.
“Seq2Seq models are widely used for tasks like machine translation and text summarization, where the input text is transformed into another text.”