IwasakiYuuki/Bert-abstractive-text-summarization

This project is a legacy implementation from the early BERT era (circa 2018-2019). While it was likely a useful reference for applying BERT to Japanese abstractive summarization at the time, it has been entirely superseded by modern LLMs and specialized sequence-to-sequence models like T5, BART, and Llama-3 variants specifically tuned for Japanese (e.g., Swallow). With only 49 stars and zero recent activity, it lacks the momentum or community to compete with the Hugging Face ecosystem or frontier laboratory APIs. Its defensibility is near zero as the technique is now a standard textbook example of encoder-decoder fine-tuning. For any production use case, a developer would choose a pre-trained model from a provider like OpenAI or a more modern open-weights model like 'japanese-t5-base' or 'Llama-3-8B-Instruct-Japanese' over this repository. It serves primarily as a historical reference for how BERT was adapted for generation before the dominance of decoder-only and unified T5 architectures.