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Synatra Mixtral 8x7B AWQ by LoneStriker

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Model Card on HF 🤗: https://huggingface.co/LoneStriker/Synatra-Mixtral-8x7B-AWQ 

Synatra Mixtral 8x7B AWQ Benchmarks

LLME Score: 0.1478
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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Synatra Mixtral 8x7B AWQ Parameters and Internals

Additional Notes 
The model showcases superior comprehension and inference capabilities.
Supported Languages 
ko (unknown), en (unknown)
Training Details 
Methodology:
fine-tuned version using Korean datasets
Hardware Used:
A100 80GB * 6
Input Output 
Input Format:
Alpaca format: '### Instruction: {input} ### Response: {output}'
LLM NameSynatra Mixtral 8x7B AWQ
Repository 🤗https://huggingface.co/LoneStriker/Synatra-Mixtral-8x7B-AWQ 
Model Size6.5b
Required VRAM24.7 GB
Updated2025-06-09
MaintainerLoneStriker
Model Typemixtral
Model Files  10.0 GB: 1-of-3   10.0 GB: 2-of-3   4.7 GB: 3-of-3
Supported Languagesko en
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.1
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat16
Synatra Mixtral 8x7B AWQ (LoneStriker/Synatra-Mixtral-8x7B-AWQ)

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/Synatra-Mixtral-8x7B-AWQ.

Rank the Synatra Mixtral 8x7B AWQ Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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