yaserkl/RLSeq2Seq
Deep Reinforcement Learning For Sequence to Sequence Models
This project provides advanced methods for abstractive text summarization. It takes long-form articles, such as news stories, and condenses them into shorter summaries. Researchers and developers working on natural language processing tasks, particularly those focused on improving sequence-to-sequence models for text generation, would find this useful.
768 stars. No commits in the last 6 months.
Use this if you are a researcher or advanced practitioner experimenting with reinforcement learning techniques to overcome common limitations in sequence-to-sequence models for tasks like text summarization.
Not ideal if you need a plug-and-play solution for text summarization without deep technical expertise or if you require an actively maintained project.
Stars
768
Forks
161
Language
Python
License
MIT
Category
Last pushed
Mar 24, 2023
Commits (30d)
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