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Medorca 2x7b by Technoculture

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  Merged Model   Autotrain compatible   Endpoints compatible   Epfl-llm/meditron-7b   Microsoft/orca-2-7b   Mixtral   Moe   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Technoculture/Medorca-2x7b 

Medorca 2x7b Benchmarks

ARC: 54.1 vs 96.7 (so35)-44.1%
HellaSwag: 76.04 vs 95.3 (gpt4)-20.2%
MMLU: 53.3 vs 88.3 (so35)-39.6%
TruthfulQA: 48.04 vs 59 (gpt4)-18.6%
WinoGrande: 74.51 vs 87.5 (gpt4)-14.8%
GSM8K: 20.62 vs 96.4 (so35)-78.6%
LLME Score: 0.17321
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Medorca 2x7b (Technoculture/Medorca-2x7b)
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Medorca 2x7b Parameters and Internals

Model Type 
MoE (Mixture of Experts)
LLM NameMedorca 2x7b
Repository 🤗https://huggingface.co/Technoculture/Medorca-2x7b 
Merged ModelYes
Model Size11.1b
Required VRAM35.6 GB
Updated2025-09-20
MaintainerTechnoculture
Model Typemixtral
Model Files  10.0 GB: 1-of-2   10.0 GB: 1-of-3   3.5 GB: 2-of-2   10.0 GB: 2-of-3   2.1 GB: 3-of-3
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<s>
Vocabulary Size32003
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than Technoculture/Medorca-2x7b.

Rank the Medorca 2x7b 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 v20241124
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