olmOCR

olmOCR is an open source toolkit developed by the Allen Institute for Artificial Intelligence (AI2), designed to linearize PDF documents for use in the training of large language models (LLM). This toolkit solves the problem that traditional PDF documents have complex structures and are difficult to directly use for model training by converting PDF documents into a format suitable for LLM processing. It supports a variety of functions, including natural text parsing, multi-version comparison, language filtering, and SEO spam removal. The main advantage of olmOCR is that it can efficiently process a large number of PDF documents and improve the accuracy and efficiency of text parsing through optimized prompt strategies and model fine-tuning. This toolkit is intended for researchers and developers who need to process large amounts of PDF data, especially in the fields of natural language processing and machine learning.

olmOCR is primarily intended for researchers and developers who need to process large amounts of PDF documents, especially in the fields of natural language processing and machine learning. It is suitable for users who need to convert PDF documents into datasets suitable for LLM training, as well as for teams who need to efficiently process and parse PDF text.