OLMo 7B Twin 2T by allenai

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  Arxiv:2302.13971   Arxiv:2402.00838   Autotrain compatible   Custom code   Dataset:allenai/dolma   En   Hf olmo   Pytorch   Region:us   Safetensors
Model Card on HF ๐Ÿค—: https://huggingface.co/allenai/OLMo-7B-Twin-2T 

OLMo 7B Twin 2T Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
OLMo 7B Twin 2T (allenai/OLMo-7B-Twin-2T)

OLMo 7B Twin 2T Parameters and Internals

Model Type 
transformer, autoregressive language model
Supported Languages 
en (high)
Training Details 
Data Sources:
Dolma dataset
Data Volume:
2 Trillion tokens
Methodology:
Uses a Transformer architecture
Context Length:
2048
Hardware Used:
MI250X (LUMI Supercomputer), A100-40GB (MosaicML)
Model Architecture:
4096 hidden size, 32 layers, 32 attention heads
Input Output 
Accepted Modalities:
text
LLM NameOLMo 7B Twin 2T
Repository ๐Ÿค—https://huggingface.co/allenai/OLMo-7B-Twin-2T 
Model Size7b
Required VRAM27.6 GB
Updated2025-01-24
Maintainerallenai
Model Typehf_olmo
Model Files  27.6 GB   27.6 GB
Supported Languagesen
Model ArchitectureOLMoForCausalLM
Licenseapache-2.0
Transformers Version4.36.2
Tokenizer ClassOLMoTokenizer
Padding Token<|padding|>
Vocabulary Size50280

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Note: green Score (e.g. "73.2") means that the model is better than allenai/OLMo-7B-Twin-2T.

Rank the OLMo 7B Twin 2T Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Data Analysis and Insight Generation  
Text Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227