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Mistral Ko Inst Dev by beomi

 »  All LLMs  »  beomi  »  Mistral Ko Inst Dev   URL Share it on

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  Autotrain compatible   Conversational Dataset:heegyu/kowiki-sentence...   Dataset:heegyu/kowikitext   En   Endpoints compatible   Ko   Mistral   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/beomi/Mistral-Ko-Inst-dev 

Mistral Ko Inst Dev Benchmarks

LLME Score: 0.14118
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral Ko Inst Dev (beomi/Mistral-Ko-Inst-dev)
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Mistral Ko Inst Dev Parameters and Internals

Model Type 
text generation, natural language understanding
Use Cases 
Areas:
Research, Experimental applications
Applications:
Korean language processing, NLU tasks
Primary Use Cases:
Answering in Korean using English knowledge
Limitations:
Designed for experimental use, contents updated without notice, Minimal dataset usage may impact performance and accuracy
Considerations:
Use the repository with a specific git hash for stable results
Additional Notes 
This is an experimental repository and content updates may occur without notice.
Supported Languages 
ko (proficient), en (proficient)
Training Details 
Data Sources:
heegyu/kowikitext, heegyu/kowiki-sentences
Data Volume:
Minimal dataset used: Korean Wikipedia only
Methodology:
Adapt new Korean vocabulary, maintain NLU capability of Mistral-Instruct model
Input Output 
Input Format:
Text in Korean or English
Accepted Modalities:
text
Output Format:
Generated text responses in Korean or English
LLM NameMistral Ko Inst Dev
Repository 🤗https://huggingface.co/beomi/Mistral-Ko-Inst-dev 
Model Size7.4b
Required VRAM14.8 GB
Updated2025-10-10
Maintainerbeomi
Model Typemistral
Model Files  5.0 GB: 1-of-3   4.9 GB: 2-of-3   4.9 GB: 3-of-3
Supported Languagesko en
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size46592
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than beomi/Mistral-Ko-Inst-dev.

Rank the Mistral Ko Inst Dev 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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