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Gemma Ko Merge by Gunulhona

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  Merged Model   Autotrain compatible Base model:lemon07r/gemma-2-at... Base model:rtzr/ko-gemma-2-9b-... Base model:wzhouad/gemma-2-9b-...   Conversational   Endpoints compatible   Gemma2   Gguf   Model-index   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Gunulhona/Gemma-Ko-Merge 

Gemma Ko Merge Benchmarks

MMLU Pro: 31.99
GPQA: 11.41
MUSR: 9.12
BBH: 38.79
IFEval: 64.16 vs 88 (so35)-27.1%
MATH Lvl 5: 18.81
LLME Score: 0.26945
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma Ko Merge (Gunulhona/Gemma-Ko-Merge)
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Gemma Ko Merge Parameters and Internals

Additional Notes 
This model is a merge of pre-trained language models created using mergekit. The merge was conducted using the breadcrumbs_ties merge method.
LLM NameGemma Ko Merge
Repository 🤗https://huggingface.co/Gunulhona/Gemma-Ko-Merge 
Base Model(s)  Gemma 2 Ataraxy 9B   Gemma 2 9B It WPO HB   Ko Gemma 2 9B It   ...emma9 On Korean Summary Events   Ko Gemma 2 9B It   lemon07r/Gemma-2-Ataraxy-9B   wzhouad/gemma-2-9b-it-WPO-HB   rtzr/ko-gemma-2-9b-it   ghost613/gemma9_on_korean_summary_events   rtzr/ko-gemma-2-9b-it
Merged ModelYes
Model Size9b
Required VRAM20.4 GB
Updated2025-09-23
MaintainerGunulhona
Model Typegemma2
Model Files  9.8 GB   1.8 GB: 1-of-11   1.9 GB: 2-of-11   2.0 GB: 3-of-11   2.0 GB: 4-of-11   2.0 GB: 5-of-11   2.0 GB: 6-of-11   2.0 GB: 7-of-11   2.0 GB: 8-of-11   2.0 GB: 9-of-11   2.0 GB: 10-of-11   0.7 GB: 11-of-11
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureGemma2ForCausalLM
Context Length8192
Model Max Length8192
Transformers Version4.45.0.dev0
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than Gunulhona/Gemma-Ko-Merge.

Rank the Gemma Ko Merge Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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