SauerkrautLM Mixtral 8x7B Instruct GGUF by TheBloke

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  Augmentation Base model:quantized:vagosolut... Base model:vagosolutions/sauer...   Conversational Dataset:argilla/distilabel-mat...   De   Dpo   En   Es   Finetuned   Fr   German   Gguf   Instruct   It   Mistral   Mixtral   Moe   Quantized   Region:us

SauerkrautLM Mixtral 8x7B Instruct GGUF Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

SauerkrautLM Mixtral 8x7B Instruct GGUF Parameters and Internals

Model Type 
mixtral
Use Cases 
Primary Use Cases:
text generation
Supported Languages 
English (unknown), German (unknown), French (unknown), Italian (unknown), Spanish (unknown)
Training Details 
Data Sources:
argilla/distilabel-math-preference-dpo
Methodology:
Mixture of Experts (MoE) Model
Model Architecture:
based on mistralai/Mixtral-8x7B-Instruct-v0.1
Input Output 
Input Format:
[INST] {prompt} [/INST]
Accepted Modalities:
text
LLM NameSauerkrautLM Mixtral 8x7B Instruct GGUF
Repository ๐Ÿค—https://huggingface.co/TheBloke/SauerkrautLM-Mixtral-8x7B-Instruct-GGUF 
Model NameSauerkrautLM Mixtral 8X7B Instruct
Model CreatorVAGO solutions
Base Model(s)  ...rkrautLM Mixtral 8x7B Instruct   VAGOsolutions/SauerkrautLM-Mixtral-8x7B-Instruct
Required VRAM15.6 GB
Updated2024-11-22
MaintainerTheBloke
Model Typemixtral
Instruction-BasedYes
Model Files  15.6 GB   20.4 GB   26.4 GB   26.4 GB   32.2 GB   32.2 GB   38.4 GB   49.6 GB
Supported Languagesen de fr it es
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModel
Licenseapache-2.0
SauerkrautLM Mixtral 8x7B Instruct GGUF (TheBloke/SauerkrautLM-Mixtral-8x7B-Instruct-GGUF)

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Dolphin 2.7 Mixtral 8x7b GGUF0K / 15.6 GB11299134
Phi 3 Mini 4K Instruct GGUF0K / 1.4 GB166316
Spydaz Web AI 0K / 4.4 GB1233
Mixtral AI Llava 4bit0K / 14.4 GB19211
...i 3 Mini 4K Instruct V0.3 GGUF0K / 1.4 GB2275
Phi 3 Mini 4K Instruct0K / 2.3 GB260
Dolphin 2 6 Phi 2 GGUF0K / 1.2 GB611070
Dre Phi Gguf0K / 2.3 GB160
Note: green Score (e.g. "73.2") means that the model is better than TheBloke/SauerkrautLM-Mixtral-8x7B-Instruct-GGUF.

Rank the SauerkrautLM Mixtral 8x7B Instruct GGUF 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 v20241110