santhoshkolloju/Abstractive-Summarization-With-Transfer-Learning
An abstractive summarization model that uses pretrained BERT as encoder and trains a Transformer decoder from scratch for text generation.
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This project implements neural abstractive summarization by leveraging BERT’s pretrained encoder via transfer learning. The architecture replaces the encoder with BERT and trains a Transformer decoder from scratch, avoiding the sequential processing bottleneck of LSTM-based models. The system includes preprocessing, training, and inference components with a Flask server for serving predictions.
Frequently asked
- What is santhoshkolloju/Abstractive-Summarization-With-Transfer-Learning?
- An abstractive summarization model that uses pretrained BERT as encoder and trains a Transformer decoder from scratch for text generation.
- Is Abstractive-Summarization-With-Transfer-Learning open source?
- Yes — santhoshkolloju/Abstractive-Summarization-With-Transfer-Learning is an open-source project tracked on heatdrop.
- What language is Abstractive-Summarization-With-Transfer-Learning written in?
- santhoshkolloju/Abstractive-Summarization-With-Transfer-Learning is primarily written in Python.
- How popular is Abstractive-Summarization-With-Transfer-Learning?
- santhoshkolloju/Abstractive-Summarization-With-Transfer-Learning has 412 stars on GitHub.
- Where can I find Abstractive-Summarization-With-Transfer-Learning?
- santhoshkolloju/Abstractive-Summarization-With-Transfer-Learning is on GitHub at https://github.com/santhoshkolloju/Abstractive-Summarization-With-Transfer-Learning.