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MultiVerse 70B by MTSAIR

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Model Card on HF 🤗: https://huggingface.co/MTSAIR/MultiVerse_70B 

MultiVerse 70B Benchmarks

MMLU Pro: 42.89
GPQA: 13.87
MUSR: 18.82
BBH: 46.14
IFEval: 52.49 vs 88 (so35)-40.4%
ARC: 78.58 vs 96.7 (so35)-18.7%
HellaSwag: 89.74 vs 95.3 (gpt4)-5.8%
MMLU: 78.27 vs 88.3 (so35)-11.4%
TruthfulQA: 75.09 vs 59 (gpt4)27.3%
WinoGrande: 87.37 vs 87.5 (gpt4)-0.1%
GSM8K: 76.8 vs 96.4 (so35)-20.3%
MATH Lvl 5: 17.82
LLME Score: 0.32218
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MultiVerse 70B (MTSAIR/MultiVerse_70B)

MultiVerse 70B Parameters and Internals

Model Type 
text-generation
Additional Notes 
The multiverse training method used is a novel technique under development.
Training Details 
Methodology:
multiverse training method
LLM NameMultiVerse 70B
Repository 🤗https://huggingface.co/MTSAIR/MultiVerse_70B 
Model Size70b
Required VRAM144.5 GB
Updated2024-12-23
MaintainerMTSAIR
Model Typellama
Model Files  4.8 GB: 1-of-30   5.0 GB: 2-of-30   5.0 GB: 3-of-30   4.8 GB: 4-of-30   4.8 GB: 5-of-30   4.8 GB: 6-of-30   5.0 GB: 7-of-30   5.0 GB: 8-of-30   4.8 GB: 9-of-30   4.8 GB: 10-of-30   4.8 GB: 11-of-30   5.0 GB: 12-of-30   5.0 GB: 13-of-30   4.8 GB: 14-of-30   4.8 GB: 15-of-30   4.8 GB: 16-of-30   5.0 GB: 17-of-30   5.0 GB: 18-of-30   4.8 GB: 19-of-30   4.8 GB: 20-of-30   4.8 GB: 21-of-30   5.0 GB: 22-of-30   5.0 GB: 23-of-30   4.8 GB: 24-of-30   4.8 GB: 25-of-30   4.8 GB: 26-of-30   5.0 GB: 27-of-30   5.0 GB: 28-of-30   4.8 GB: 29-of-30   2.9 GB: 30-of-30
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Tokenizer ClassGPT2Tokenizer
Padding Token<
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

Quantized Models of the MultiVerse 70B

Model
Likes
Downloads
VRAM
MultiVerse 70B AWQ29241 GB

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Note: green Score (e.g. "73.2") means that the model is better than MTSAIR/MultiVerse_70B.

Rank the MultiVerse 70B Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Release v20241217
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