8 citations · 15 across the 5 of their papers we have counts for
5 papers
H2OVL-Mississippi Vision Language Models Technical Report
Shaikat Galib, Shanshan Wang, Guanshuo Xu +4
Smaller vision-language models (VLMs) are becoming increasingly important for privacy-focused, on-device applications due to their ability to run efficiently on consumer hardware f…
H2O-Danube3 Technical Report
Pascal Pfeiffer, Philipp Singer, Yauhen Babakhin +3
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…
H2O-Danube-1.8B Technical Report
Philipp Singer, Pascal Pfeiffer, Yauhen Babakhin +4
We present H2O-Danube, a series of small 1.8B language models consisting of H2O-Danube-1.8B, trained on 1T tokens, and the incremental improved H2O-Danube2-1.8B trained on an addit…
h2oGPT: Democratizing Large Language Models
Arno Candel, Jon McKinney, Philipp Singer +12
Applications built on top of Large Language Models (LLMs) such as GPT-4 represent a revolution in AI due to their human-level capabilities in natural language processing. However,…
Backtesting the predictability of COVID-19
Dmitry Gordeev, Philipp Singer, Marios Michailidis +2
The advent of the COVID-19 pandemic has instigated unprecedented changes in many countries around the globe, putting a significant burden on the health sectors, affecting the macro…