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Medius Erebus Magnum 14B by underwoods

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  Autotrain compatible   Axolotl Base model:finetune:qwen/qwen2...   Base model:qwen/qwen2.5-14b   Conversational   Endpoints compatible   Generated from trainer   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/underwoods/medius-erebus-magnum-14b 

Medius Erebus Magnum 14B Benchmarks

LLME Score: 0.23166
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Medius Erebus Magnum 14B (underwoods/medius-erebus-magnum-14b)

Medius Erebus Magnum 14B Parameters and Internals

LLM NameMedius Erebus Magnum 14B
Repository 🤗https://huggingface.co/underwoods/medius-erebus-magnum-14b 
Base Model(s)  Qwen/Qwen2.5-14B   Qwen/Qwen2.5-14B
Model Size14b
Required VRAM29.7 GB
Updated2025-03-24
Maintainerunderwoods
Model Typeqwen2
Model Files  5.0 GB: 1-of-6   5.0 GB: 2-of-6   5.0 GB: 3-of-6   5.0 GB: 4-of-6   5.0 GB: 5-of-6   4.7 GB: 6-of-6
Model ArchitectureQwen2ForCausalLM
Context Length131072
Model Max Length131072
Transformers Version4.45.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151665
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than underwoods/medius-erebus-magnum-14b.

Rank the Medius Erebus Magnum 14B 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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