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Multi Verse Model by MTSAIR

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  Autotrain compatible   Conversational   En   Endpoints compatible   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/MTSAIR/multi_verse_model 

Multi Verse Model Benchmarks

ARC: 72.87 vs 96.7 (so35)-24.6%
HellaSwag: 89.2 vs 95.3 (gpt4)-6.4%
MMLU: 64.4 vs 88.3 (so35)-27.1%
TruthfulQA: 77.92 vs 59 (gpt4)32.1%
WinoGrande: 84.77 vs 87.5 (gpt4)-3.1%
GSM8K: 71.27 vs 96.4 (so35)-26.1%
LLME Score: 0.24102
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Multi Verse Model (MTSAIR/multi_verse_model)

Multi Verse Model Parameters and Internals

Additional Notes 
The model is characterized as a 'learning bot' with an innovative training method aimed at continuous learning and growth in AI.
Supported Languages 
en (proficient)
Training Details 
Methodology:
cutting-edge training method
LLM NameMulti Verse Model
Repository 🤗https://huggingface.co/MTSAIR/multi_verse_model 
Model Size7.2b
Required VRAM14.4 GB
Updated2024-12-21
MaintainerMTSAIR
Model Typemistral
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Supported Languagesen
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.39.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16

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

Rank the Multi Verse Model 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 v20241217
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