H2O-Danube3 Technical Report
Authors: name: Pascal Pfeiffer, name: Philipp Singer, name: Yauhen Babakhin, name: Gabor Fodor, name: Nischay Dhankhar, name: Sri Satish Ambati

We present H2O-Danube3, a series of small language models consisting of
H2O-Danube3-4B, trained on 6T tokens and H2O-Danube3-500M, trained on 4T
tokens. Our models are pre-trained on high quality Web data consisting of
primarily English tokens in three stages with different data mixes before final
supervised tuning for chat version. The models exhibit highly competitive
metrics across a multitude of academic, chat, and fine-tuning benchmarks.
Thanks to its compact architecture, H2O-Danube3 can be efficiently run on a
modern smartphone, enabling local inference and rapid processing capabilities
even on mobile devices. We make all models openly available under Apache 2.0
license further democratizing LLMs to a wider audience economically.