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OLMo 1B Hf by allenai

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OLMo 1B Hf is an open-source language model by allenai. Features: 1b LLM, VRAM: 4.7GB, Context: 2K, License: apache-2.0, HF Score: 36.7, LLM Explorer Score: 0.25, Arc: 34.6, HellaSwag: 63.6, MMLU: 26.3, TruthfulQA: 32.9, WinoGrande: 61.1, GSM8K: 1.9.

  Arxiv:2302.13971   Arxiv:2402.00838   Dataset:allenai/dolma   En   Endpoints compatible   Olmo   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/allenai/OLMo-1B-hf 

OLMo 1B Hf Benchmarks

MMLU Pro: 1.93
GPQA: 1.57
MUSR: 9.56
BBH: 3.2
IFEval: 21.82 vs 88 (so35)-75.2%
ARC: 34.56 vs 96.7 (so35)-64.3%
HellaSwag: 63.6 vs 95.3 (gpt4)-33.3%
MMLU: 26.31 vs 88.3 (so35)-70.2%
TruthfulQA: 32.92 vs 59 (gpt4)-44.2%
WinoGrande: 61.09 vs 87.5 (gpt4)-30.2%
GSM8K: 1.9 vs 96.4 (so35)-98%
MATH Lvl 5: 1.74
LLME Score: 0.24516
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
OLMo 1B Hf (allenai/OLMo-1B-hf)
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OLMo 1B Hf Parameters and Internals

Model Type 
Autoregressive Language Model, Transformer
Use Cases 
Areas:
Research, Commercial Applications
Applications:
Language Modeling
Primary Use Cases:
Text Generation
Limitations:
Prone to generate false or harmful content
Considerations:
Consider risks of applications due to potential bias
Additional Notes 
The model supports quantization for faster inference.
Supported Languages 
en (English)
Training Details 
Data Sources:
Dolma
Data Volume:
Trained on 3 trillion tokens
Context Length:
2048
Model Architecture:
Transformer style
Input Output 
Accepted Modalities:
text
LLM NameOLMo 1B Hf
Repository 🤗https://huggingface.co/allenai/OLMo-1B-hf 
Model Size1b
Required VRAM4.7 GB
Updated2026-03-29
Maintainerallenai
Model Typeolmo
Model Files  4.7 GB
Supported Languagesen
Model ArchitectureOlmoForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.40.0
Tokenizer ClassGPTNeoXTokenizer
Padding Token<|padding|>
Vocabulary Size50304
Torch Data Typefloat32

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Rank the OLMo 1B Hf 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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