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Open-weight H2O-Danube2-1.8B

Tiny high-performance GenAI LLM

#1 foundation model on Hugging Face LLM Leaderboard for <2B range


This model is ideal for fine-tuning on domain-specific datasets, economically efficient for inference and training, and easily embedded on edge devices like mobile phones and drones. It outperforms leading competitors such as Microsoft Phi-2 and Google Gemma 2, offering significant economic and deployment advantages for enterprise and edge computing applications.

  • Cost savings on the Platform. 200x cheaper on query cost.
  • Serve more users. Better accuracy with up to 100% cheaper on document processing.
display of a laptop, desktop, tablet, cell phone, and IoT devices display of a laptop, desktop, tablet, cell phone, and IoT devices

Early H2O Danube2 applications

PII Detection

Detect patterns of personal identification Kaggle

LLM Generated Content Detection

Easier to detect human generated

Guardrails LLMs and Gateway LLM

LLM Safety with an LLM

Own Your Data

Post-train and fine-tune LLMs on your tokens for best price / performance on commodity hardware

On-device, offline use cases

Content Generation: Writing and editing in airplane mode.

Research: Analyzing and learning in offline mode. Accessing critical information while stranded.

Guardrails & Gateway: Confirm a user's question and input is valid and safe before sending to a more expensive model.

Entertainment: Reading pop culture trivia, learning historical facts, creating a social content calendar.

Remote Field Work (IoT): Technicians can get data from IoT sensors on their mobile devices in the field even during service blackouts.