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Synatra 7B V0.3 RP EXL2 by IHaBiS

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  Autotrain compatible   Conversational   Endpoints compatible   Exl2   Instruct   Ko   Mistral   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/IHaBiS/Synatra-7B-v0.3-RP-exl2 

Synatra 7B V0.3 RP EXL2 Benchmarks

ARC: 62.2 vs 96.7 (so35)-35.7%
HellaSwag: 82.29 vs 95.3 (gpt4)-13.7%
MMLU: 60.8 vs 88.3 (so35)-31.1%
TruthfulQA: 52.64 vs 59 (gpt4)-10.8%
WinoGrande: 76.48 vs 87.5 (gpt4)-12.6%
GSM8K: 21.15 vs 96.4 (so35)-78.1%
LLME Score: 0.13729
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Synatra 7B V0.3 RP EXL2 (IHaBiS/Synatra-7B-v0.3-RP-exl2)
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Synatra 7B V0.3 RP EXL2 Parameters and Internals

Model Type 
text-generation
Additional Notes 
The model is intended for use in non-commercial applications and follows the ChatML instruction format.
Training Details 
Hardware Used:
A6000 48GB * 8
Input Output 
Input Format:
ChatML format
LLM NameSynatra 7B V0.3 RP EXL2
Repository 🤗https://huggingface.co/IHaBiS/Synatra-7B-v0.3-RP-exl2 
Base Model(s)  maywell/Synatra-7B-v0.3-RP   maywell/Synatra-7B-v0.3-RP
Model Size7b
Required VRAM7.4 GB
Updated2025-09-23
MaintainerIHaBiS
Model Typemistral
Instruction-BasedYes
Model Files  7.4 GB
Supported Languagesko
Quantization Typeexl2
Model ArchitectureMistralForCausalLM
Licensecc-by-nc-4.0
Context Length32768
Model Max Length32768
Transformers Version4.34.1
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32002
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than IHaBiS/Synatra-7B-v0.3-RP-exl2.

Rank the Synatra 7B V0.3 RP EXL2 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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Release v20241124
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