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OPT 6.7B Nerybus Mix by KoboldAI

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  Autotrain compatible   En   Opt   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/KoboldAI/OPT-6.7B-Nerybus-Mix 

OPT 6.7B Nerybus Mix Benchmarks

ARC: 39.16 vs 96.7 (so35)-59.5%
HellaSwag: 68.63 vs 95.3 (gpt4)-28%
MMLU: 24.47 vs 88.3 (so35)-72.3%
TruthfulQA: 34.84 vs 59 (gpt4)-40.9%
WinoGrande: 65.11 vs 87.5 (gpt4)-25.6%
GSM8K: 0.76 vs 96.4 (so35)-99.2%
LLME Score: 0.12118
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
OPT 6.7B Nerybus Mix (KoboldAI/OPT-6.7B-Nerybus-Mix)
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OPT 6.7B Nerybus Mix Parameters and Internals

Additional Notes 
This experimental model combines the weights of two source models with a parameter-wise 50/50 blend, producing coherent outputs though less impressive than the 2.7B variant.
LLM NameOPT 6.7B Nerybus Mix
Repository 🤗https://huggingface.co/KoboldAI/OPT-6.7B-Nerybus-Mix 
Model Size6.7b
Required VRAM13.7 GB
Updated2025-09-23
MaintainerKoboldAI
Model Typeopt
Model Files  3.1 GB: 1-of-5   3.1 GB: 2-of-5   3.1 GB: 3-of-5   3.0 GB: 4-of-5   1.4 GB: 5-of-5
Supported Languagesen
Model ArchitectureOPTForCausalLM
Licenseother
Context Length2048
Model Max Length2048
Transformers Version4.24.0
Tokenizer ClassGPT2Tokenizer
Beginning of Sentence Token</s>
End of Sentence Token</s>
Unk Token</s>
Vocabulary Size50265
Torch Data Typefloat16
Activation Functionrelu
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than KoboldAI/OPT-6.7B-Nerybus-Mix.

Rank the OPT 6.7B Nerybus Mix Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
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Release v20241124
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