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H2o Danube 1.8B Base by h2oai

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H2o Danube 1.8B Base is an open-source language model by h2oai. Features: 1.8b LLM, VRAM: 3.7GB, Context: 16K, License: apache-2.0, LLM Explorer Score: 0.16, Arc: 39.4, HellaSwag: 69.6, MMLU: 25.9, GSM8K: 1.4.

  Arxiv:2401.16818   En   Endpoints compatible   Gpt   Mistral   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/h2oai/h2o-danube-1.8b-base 

H2o Danube 1.8B Base Benchmarks

ARC: 39.42 vs 96.7 (so35)-59.2%
HellaSwag: 69.58 vs 95.3 (gpt4)-27%
MMLU: 25.94 vs 88.3 (so35)-70.6%
GSM8K: 1.44 vs 96.4 (so35)-98.5%
LLME Score: 0.15695
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
H2o Danube 1.8B Base (h2oai/h2o-danube-1.8b-base)
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H2o Danube 1.8B Base Parameters and Internals

Model Type 
GPT, Large Language Model, Text Generation
Use Cases 
Areas:
Research, Commercial Applications
Limitations:
May produce biased, racist, offensive, or otherwise inappropriate content
Considerations:
Use responsibly and ethically.
Additional Notes 
This is a pre-trained foundation model requiring fine-tuning for specific tasks.
Supported Languages 
English (proficient)
Training Details 
Methodology:
We adjust the Llama 2 architecture with sliding window attention from mistral.
Context Length:
16384
Model Architecture:
Llama 2 adapted architecture with sliding window attention.
LLM NameH2o Danube 1.8B Base
Repository 🤗https://huggingface.co/h2oai/h2o-danube-1.8b-base 
Model Size1.8b
Required VRAM3.7 GB
Updated2026-05-21
Maintainerh2oai
Model Typemistral
Model Files  3.7 GB
Supported Languagesen
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length16384
Model Max Length16384
Transformers Version4.36.1
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than h2oai/h2o-danube-1.8b-base.

Rank the H2o Danube 1.8B Base Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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