mlsanityData to 14 Oct 2026

H2O-Danube-1.8B Technical Report

arXiv 2401.16818 ↗First posted 30 Jan 2024cs.CL cs.LGcited by 9

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Abstract (arXiv)

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 additional 2T tokens. Our models exhibit highly competitive metrics across a multitude of benchmarks and, as of the time of this writing, H2O-Danube2-1.8B achieves the top ranking on Open LLM Leaderboard for all models below the 2B parameter range. The models follow core principles of LLama 2 and Mistral, and we leverage and refine various techniques for pre-training large language models. We additionally release chat models trained with supervised fine-tuning followed by direct preference optimization. We make all models openly available under Apache 2.0 license further democratizing LLMs to a wider audience economically.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 34 of its 43 references that are in the map. First posted on arXiv 30 Jan 2024.

Builds on

34 of 43 references.

References · 34

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22 more
  1. 2019HellaSwag: Can a Machine Really Finish Your Sentence?cited by 4,100
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 4; 2025: 4; 2026: 1.

9 papers.

Similar, not cited

Close in wording, no citation either way

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