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BioLlama Ko 8B by iRASC

 »  All LLMs  »  iRASC  »  BioLlama Ko 8B   URL Share it on

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  Merged Model   Arxiv:2306.01708   Arxiv:2311.03099   Autotrain compatible Base model:beomi/llama-3-open-... Base model:probemedicalyonseim...   Conversational   Dataset:sean0042/kormedmcqa   Endpoints compatible   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/iRASC/BioLlama-Ko-8B 

BioLlama Ko 8B Benchmarks

LLME Score: 0.19201
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
BioLlama Ko 8B (iRASC/BioLlama-Ko-8B)

BioLlama Ko 8B Parameters and Internals

Model Type 
Language Model, Text Generation
Additional Notes 
Model merged using DARE TIES. Parameters: density 0.8, weight 0.45.
Training Details 
Data Sources:
sean0042/KorMedMCQA
Methodology:
DARE TIES
Model Architecture:
Merge of pre-trained models
LLM NameBioLlama Ko 8B
Repository 🤗https://huggingface.co/iRASC/BioLlama-Ko-8B 
Base Model(s)  Llama 3 Open Ko 8B   Medllama3 V20   beomi/Llama-3-Open-Ko-8B   ProbeMedicalYonseiMAILab/medllama3-v20
Merged ModelYes
Model Size8b
Required VRAM16 GB
Updated2025-06-01
MaintaineriRASC
Model Typellama
Model Files  3.0 GB: 1-of-6   3.0 GB: 2-of-6   2.9 GB: 3-of-6   2.9 GB: 4-of-6   2.9 GB: 5-of-6   1.3 GB: 6-of-6
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.41.1
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|eot_id|>
Vocabulary Size128256
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than iRASC/BioLlama-Ko-8B.

Rank the BioLlama Ko 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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