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Frankenstein MoE En 10.7Bx4 by MoEMoEKKung

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  Autotrain compatible   Conversational   En   Endpoints compatible   Mixtral   Moe   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/MoEMoEKKung/Frankenstein-MoE-en-10.7Bx4 

Frankenstein MoE En 10.7Bx4 Benchmarks

LLME Score: 0.14881
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Frankenstein MoE En 10.7Bx4 (MoEMoEKKung/Frankenstein-MoE-en-10.7Bx4)
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Frankenstein MoE En 10.7Bx4 Parameters and Internals

Model Type 
MoE
Additional Notes 
Evals in progress.
Supported Languages 
en (proficient)
Training Details 
Data Sources:
H6 trainset, trufulqa generated by GPT-4
Methodology:
To initialize the gate projection weight of the MoE layer, the H6 trainset was sampled and used.
Model Architecture:
MoE layer with gate projection weight initialization.
LLM NameFrankenstein MoE En 10.7Bx4
Repository 🤗https://huggingface.co/MoEMoEKKung/Frankenstein-MoE-en-10.7Bx4 
Model Size36.1b
Required VRAM72.3 GB
Updated2025-09-23
MaintainerMoEMoEKKung
Model Typemixtral
Model Files  9.9 GB: 1-of-8   10.0 GB: 2-of-8   10.0 GB: 3-of-8   10.0 GB: 4-of-8   10.0 GB: 5-of-8   10.0 GB: 6-of-8   10.0 GB: 7-of-8   2.4 GB: 8-of-8
Supported Languagesen
Model ArchitectureMixtralForCausalLM
Licensecc-by-nc-sa-4.0
Context Length4096
Model Max Length4096
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<s>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than MoEMoEKKung/Frankenstein-MoE-en-10.7Bx4.

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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