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Nyonic Technical Report
April 25, 2024, 5:44 p.m. | Junfeng Tian, Rui Wang, Cong Li, Yudong Zhou, Jun Liu, Jun Wang
cs.CL updates on arXiv.org arxiv.org
Abstract: This report details the development and key achievements of our latest language model designed for custom large language models. The advancements introduced include a novel Online Data Scheduler that supports flexible training data adjustments and curriculum learning. The model's architecture is fortified with state-of-the-art techniques such as Rotary Positional Embeddings, QK-LayerNorm, and a specially crafted multilingual tokenizer to enhance stability and performance. Moreover, our robust training framework incorporates advanced monitoring and rapid recovery features to …
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