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Magnum 72B V1 by alpindale

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Magnum 72B V1 Benchmarks

MMLU Pro: 49.64
GPQA: 18.79
MUSR: 15.62
BBH: 57.65
IFEval: 76.06 vs 88 (so35)-13.6%
MATH Lvl 5: 35.27
LLME Score: 0.45429
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Magnum 72B V1 Parameters and Internals

LLM NameMagnum 72B V1
Repository 🤗https://huggingface.co/alpindale/magnum-72b-v1 
Model Size72b
Required VRAM146 GB
Updated2024-07-27
Maintaineralpindale
Model Typeqwen2
Model Files  4.5 GB: 1-of-31   5.0 GB: 2-of-31   4.8 GB: 3-of-31   4.8 GB: 4-of-31   4.8 GB: 5-of-31   5.0 GB: 6-of-31   4.8 GB: 7-of-31   4.8 GB: 8-of-31   4.8 GB: 9-of-31   5.0 GB: 10-of-31   4.8 GB: 11-of-31   4.8 GB: 12-of-31   4.8 GB: 13-of-31   5.0 GB: 14-of-31   4.8 GB: 15-of-31   4.8 GB: 16-of-31   4.8 GB: 17-of-31   5.0 GB: 18-of-31   4.8 GB: 19-of-31   4.8 GB: 20-of-31   4.8 GB: 21-of-31   5.0 GB: 22-of-31   4.8 GB: 23-of-31   4.8 GB: 24-of-31   4.8 GB: 25-of-31   5.0 GB: 26-of-31   4.8 GB: 27-of-31   4.8 GB: 28-of-31   4.8 GB: 29-of-31   3.2 GB: 30-of-31   2.5 GB: 31-of-31
Supported Languagesen zh
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.40.0.dev0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace
Magnum 72B V1 (alpindale/magnum-72b-v1)

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Note: green Score (e.g. "73.2") means that the model is better than alpindale/magnum-72b-v1.

Rank the Magnum 72B V1 Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
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Text Summarization and Feature Extraction  
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Multi-Language Support and Translation  

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Release v2024072803
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