SauerkrautLM Gemma 2 2B It by VAGOsolutions

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SauerkrautLM Gemma 2 2B It Benchmarks

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 2B It (VAGOsolutions/SauerkrautLM-gemma-2-2b-it)

SauerkrautLM Gemma 2 2B It Parameters and Internals

Model Type 
Fine-tuned Language Model
Additional Notes 
The model demonstrates the potential of resource-efficient fine-tuning with Spectrum Fine-Tuning approach.
Supported Languages 
German (High), English (High), additional_languages (Improved multilinguality)
Training Details 
Data Sources:
Unique German-English Sauerkraut Mix v2
Methodology:
Spectrum Fine-Tuning targeting 25% of the model's layers. Bespoke, precision-engineered fine-tuning approach.
LLM NameSauerkrautLM Gemma 2 2B It
Repository ๐Ÿค—https://huggingface.co/VAGOsolutions/SauerkrautLM-gemma-2-2b-it 
Model Size2b
Required VRAM5.2 GB
Updated2024-12-21
MaintainerVAGOsolutions
Model Typegemma2
Model Files  5.0 GB: 1-of-2   0.2 GB: 2-of-2
Supported Languagesde en it fr pt es
Model ArchitectureGemma2ForCausalLM
Licensegemma
Context Length8192
Model Max Length8192
Transformers Version4.44.0.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-2-2b-it.

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Instruction Following and Task Automation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217