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Polyglot Ko 12.8B by EleutherAI

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Polyglot Ko 12.8B is an open-source language model by EleutherAI. Features: 12.8b LLM, VRAM: 25.8GB, Context: 2K, License: apache-2.0, HF Score: 33.3, LLM Explorer Score: 0.1, Arc: 27.1, HellaSwag: 51.7, MMLU: 26.6, TruthfulQA: 34.7, WinoGrande: 59.8, GSM8K: 0.2.

  Arxiv:2104.09864   Arxiv:2204.04541   Arxiv:2306.02254   Autotrain compatible   Endpoints compatible   Gpt neox   Ko   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/EleutherAI/polyglot-ko-12.8b 

Polyglot Ko 12.8B Benchmarks

ARC: 27.05 vs 96.7 (so35)-72%
HellaSwag: 51.68 vs 95.3 (gpt4)-45.8%
MMLU: 26.64 vs 88.3 (so35)-69.8%
TruthfulQA: 34.69 vs 59 (gpt4)-41.2%
WinoGrande: 59.75 vs 87.5 (gpt4)-31.7%
GSM8K: 0.15 vs 96.4 (so35)-99.8%
LLME Score: 0.10442
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Polyglot Ko 12.8B (EleutherAI/polyglot-ko-12.8b)
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Polyglot Ko 12.8B Parameters and Internals

Model Type 
causal-lm
Use Cases 
Areas:
research, commercial applications
Limitations:
Polyglot-Ko may not always return the most factual or accurate response., Model may produce socially unacceptable or offensive content.
Considerations:
Human curation or filtering mechanism is recommended to censor sensitive content.
Additional Notes 
Polyglot-Ko may produce socially unacceptable or offensive content.
Supported Languages 
Korean (high)
Training Details 
Data Sources:
Korean blog posts, Korean news dataset, Modu corpus, Korean patent dataset, Korean Q & A dataset, KcBert dataset, Korean fiction dataset, Korean online comments, Korean wikipedia, Clova call, Naver sentiment movie corpus, Korean hate speech dataset, Open subtitles, AIHub various tasks datasets, Standard Korean language dictionary
Data Volume:
863 GB (1.2TB before processing)
Methodology:
Trained with cross-entropy loss to maximize the likelihood of predicting the next token. Used EleutherAI GPT-NeoX framework.
Context Length:
2048
Training Time:
301,000 steps
Hardware Used:
256 A100 GPUs
Model Architecture:
40 transformer layers, model dimension 5120, feedforward dimension 20480, 40 heads, head dimension 128, RoPE applied to 64 dimensions of each head. Tokenization vocabulary of 30003.
LLM NamePolyglot Ko 12.8B
Repository 🤗https://huggingface.co/EleutherAI/polyglot-ko-12.8b 
Model Size12.8b
Required VRAM25.8 GB
Updated2025-09-23
MaintainerEleutherAI
Model Typegpt_neox
Model Files  0.9 GB: 1-of-28   0.8 GB: 2-of-28   0.8 GB: 3-of-28   1.0 GB: 4-of-28   0.9 GB: 5-of-28   1.0 GB: 6-of-28   0.9 GB: 7-of-28   1.0 GB: 8-of-28   0.9 GB: 9-of-28   1.0 GB: 10-of-28   0.9 GB: 11-of-28   1.0 GB: 12-of-28   0.9 GB: 13-of-28   1.0 GB: 14-of-28   0.9 GB: 15-of-28   1.0 GB: 16-of-28   0.9 GB: 17-of-28   1.0 GB: 18-of-28   0.9 GB: 19-of-28   1.0 GB: 20-of-28   0.9 GB: 21-of-28   1.0 GB: 22-of-28   0.9 GB: 23-of-28   1.0 GB: 24-of-28   0.9 GB: 25-of-28   1.0 GB: 26-of-28   0.9 GB: 27-of-28   0.5 GB: 28-of-28   26.0 GB
Supported Languagesko
Model ArchitectureGPTNeoXForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.29.2
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|endoftext|>
Vocabulary Size30080
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than EleutherAI/polyglot-ko-12.8b.

Rank the Polyglot Ko 12.8B 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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