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SauerkrautLM SOLAR Instruct AWQ by mayflowergmbh

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SauerkrautLM SOLAR Instruct AWQ is an open-source language model by mayflowergmbh. Features: 10.7b LLM, VRAM: 6GB, Context: 8K, License: cc-by-nc-4.0, Quantized, Instruction-Based, LLM Explorer Score: 0.11, Arc: 70.9, HellaSwag: 88.3, MMLU: 66.2, GSM8K: 64.7.

  4-bit   Awq   Conversational   Endpoints compatible   Instruct   Llama   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/mayflowergmbh/SauerkrautLM-SOLAR-Instruct-awq 

SauerkrautLM SOLAR Instruct AWQ Benchmarks

ARC: 70.9 vs 96.7 (so35)-26.7%
HellaSwag: 88.3 vs 95.3 (gpt4)-7.3%
MMLU: 66.15 vs 88.3 (so35)-25.1%
GSM8K: 64.67 vs 96.4 (so35)-32.9%
LLME Score: 0.11384
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
SauerkrautLM SOLAR Instruct AWQ (mayflowergmbh/SauerkrautLM-SOLAR-Instruct-awq)
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SauerkrautLM SOLAR Instruct AWQ Parameters and Internals

LLM NameSauerkrautLM SOLAR Instruct AWQ
Repository 🤗https://huggingface.co/mayflowergmbh/SauerkrautLM-SOLAR-Instruct-awq 
Model Size10.7b
Required VRAM6 GB
Updated2026-05-26
Maintainermayflowergmbh
Model Typellama
Instruction-BasedYes
Model Files  6.0 GB
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licensecc-by-nc-4.0
Context Length8192
Model Max Length8192
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat16

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Rank the SauerkrautLM SOLAR Instruct AWQ 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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