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SauerkrautLM Gemma 2 9B It by VAGOsolutions

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  De   En   Es   Fr   Gemma2   It   Pt   Region:us   Safetensors   Sharded   Spectrum   Tensorflow
Model Card on HF 🤗: https://huggingface.co/VAGOsolutions/SauerkrautLM-gemma-2-9b-it 

SauerkrautLM Gemma 2 9B It Benchmarks

MMLU Pro: 34.34
GPQA: 10.29
MUSR: 12.34
BBH: 43.25
IFEval: 30.24 vs 88 (so35)-65.6%
MATH Lvl 5: 0.53
LLME Score: 0.34217
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
SauerkrautLM Gemma 2 9B It (VAGOsolutions/SauerkrautLM-gemma-2-9b-it)

SauerkrautLM Gemma 2 9B It Parameters and Internals

Model Type 
text generation
Supported Languages 
de (unknown), en (unknown), it (unknown), fr (unknown), pt (unknown), es (unknown)
Training Details 
Data Sources:
German-English Sauerkraut Mix v2
Methodology:
Spectrum Fine-Tuning targeting 25% of layers
LLM NameSauerkrautLM Gemma 2 9B It
Repository 🤗https://huggingface.co/VAGOsolutions/SauerkrautLM-gemma-2-9b-it 
Model Size9b
Required VRAM18.6 GB
Updated2024-12-21
MaintainerVAGOsolutions
Model Typegemma2
Model Files  4.9 GB: 1-of-4   5.0 GB: 2-of-4   5.0 GB: 3-of-4   3.7 GB: 4-of-4
Supported Languagesde en it fr pt es
Model ArchitectureGemma2ForCausalLM
Licensegemma
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 VAGOsolutions/SauerkrautLM-gemma-2-9b-it.

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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 v20241217
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