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Autotrain Mixtral 8x7b Orpo V2 by abhishek

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Autotrain Mixtral 8x7b Orpo V2 Benchmarks

ARC: 68.77 vs 96.7 (so35)-28.9%
HellaSwag: 85.88 vs 95.3 (gpt4)-9.9%
MMLU: 70.14 vs 88.3 (so35)-20.6%
TruthfulQA: 64.33 vs 59 (gpt4)9%
WinoGrande: 82.08 vs 87.5 (gpt4)-6.2%
GSM8K: 58.98 vs 96.4 (so35)-38.8%
LLME Score: 0.21529
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Autotrain Mixtral 8x7b Orpo V2 Parameters and Internals

LLM NameAutotrain Mixtral 8x7b Orpo V2
Repository 🤗https://huggingface.co/abhishek/autotrain-mixtral-8x7b-orpo-v2 
Model Size46.7b
Required VRAM93.6 GB
Updated2024-10-18
Maintainerabhishek
Model Typemixtral
Instruction-BasedYes
Model Files  4.9 GB: 1-of-19   5.0 GB: 2-of-19   5.0 GB: 3-of-19   4.9 GB: 4-of-19   5.0 GB: 5-of-19   5.0 GB: 6-of-19   4.9 GB: 7-of-19   5.0 GB: 8-of-19   5.0 GB: 9-of-19   4.9 GB: 10-of-19   5.0 GB: 11-of-19   5.0 GB: 12-of-19   5.0 GB: 13-of-19   4.9 GB: 14-of-19   5.0 GB: 15-of-19   5.0 GB: 16-of-19   4.9 GB: 17-of-19   5.0 GB: 18-of-19   4.2 GB: 19-of-19   0.0 GB
Model ArchitectureMixtralForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.40.1
Tokenizer ClassLlamaTokenizer
Padding Token<pad>
Vocabulary Size32005
Torch Data Typebfloat16
Autotrain Mixtral 8x7b Orpo V2 (abhishek/autotrain-mixtral-8x7b-orpo-v2)

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Note: green Score (e.g. "73.2") means that the model is better than abhishek/autotrain-mixtral-8x7b-orpo-v2.

Rank the Autotrain Mixtral 8x7b Orpo V2 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 v2024072803
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