Seq2Seq Models: Decoding the Future of Text Transformation!
Published:Jan 17, 2026 08:36
•1 min read
•Qiita ML
Analysis
This article dives into the fascinating world of Seq2Seq models, a cornerstone of natural language processing! These models are instrumental in transforming text, opening up exciting possibilities in machine translation and text summarization, paving the way for more efficient and intelligent applications.
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.
Reference
“Seq2Seq models are widely used for tasks like machine translation and text summarization, where the input text is transformed into another text.”