IHUBERT is a monolingual Persian pretrained language model trained on a 45 GB curated subset of the Sepahr-Danesh collection. It uses vector-based semantic deduplication and a domain-balanced pretraining pipeline to improve corpus quality and reduce redundancy, achieving top performance in extractive question answering and strong results in NER and topic classification, though relation extraction remains a challenge.