Yi Ko DUS 9B by beomi

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  01-ai   Autotrain compatible   Doi:10.57967/hf/1707   En   Ko   Llama   Pytorch   Region:us   Safetensors   Sharded   Tensorflow   Yi   Yi-ko
Model Card on HF ๐Ÿค—: https://huggingface.co/beomi/Yi-Ko-DUS-9B 

Yi Ko DUS 9B Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Yi Ko DUS 9B (beomi/Yi-Ko-DUS-9B)

Yi Ko DUS 9B Parameters and Internals

Model Type 
text-generation
Additional Notes 
BPE vocabulary expanded to better handle Korean text.
Supported Languages 
en (English), ko (Korean)
Training Details 
Data Sources:
A mix of Korean + English online data
Data Volume:
>120B tokens
Methodology:
DUS method applied
Context Length:
4000
Hardware Used:
TPU Research Cloud
Model Architecture:
Optimized transformer architecture based on Llama-2, can be loaded via LlamaForCausalLM
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
text
Release Notes 
Version:
2024.01.29
Date:
2024-01-29
Notes:
Released Yi-Ko(KoEN)-DUS-9B model.
LLM NameYi Ko DUS 9B
Repository ๐Ÿค—https://huggingface.co/beomi/Yi-Ko-DUS-9B 
Model Size9b
Required VRAM17.9 GB
Updated2025-02-22
Maintainerbeomi
Model Typellama
Model Files  5.0 GB: 1-of-4   4.9 GB: 2-of-4   5.0 GB: 3-of-4   3.0 GB: 4-of-4
Supported Languagesen ko
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.37.1
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size78464
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than beomi/Yi-Ko-DUS-9B.

Rank the Yi Ko DUS 9B 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  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227