Chonky: Neural Semantic Chunking
Analysis
The article introduces 'Chonky,' a transformer model and library for semantic text chunking. It uses a DistilBERT model fine-tuned on a book corpus to split text into meaningful paragraphs. The approach is fully neural, unlike heuristic-based methods. The author acknowledges limitations like English-only support, downcased output, and difficulty in measuring performance improvements in RAG pipelines. The library is available on GitHub and the model on Hugging Face.
Key Takeaways
Reference
“The author proposes a fully neural approach to semantic chunking using a fine-tuned DistilBERT model. The library could be used as a text splitter module in a RAG system.”