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Hermes 2 Pro Mixtral 4x7B by Isotonic

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Hermes 2 Pro Mixtral 4x7B Benchmarks

ARC: 64.25 vs 96.7 (so35)-33.6%
HellaSwag: 82.7 vs 95.3 (gpt4)-13.2%
MMLU: 62.26 vs 88.3 (so35)-29.5%
TruthfulQA: 59.02 vs 59 (gpt4)0%
WinoGrande: 75.45 vs 87.5 (gpt4)-13.8%
GSM8K: 60.42 vs 96.4 (so35)-37.3%
LLME Score: 0.22108
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Hermes 2 Pro Mixtral 4x7B Parameters and Internals

LLM NameHermes 2 Pro Mixtral 4x7B
Repository 🤗https://huggingface.co/Isotonic/Hermes-2-Pro-Mixtral-4x7B 
Model Size24.2b
Required VRAM48.3 GB
Updated2024-09-07
MaintainerIsotonic
Model Typemixtral
Model Files  9.9 GB: 1-of-5   10.0 GB: 2-of-5   10.0 GB: 3-of-5   10.0 GB: 4-of-5   8.4 GB: 5-of-5
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Padding Token<s>
Vocabulary Size32032
Torch Data Typebfloat16
Hermes 2 Pro Mixtral 4x7B (Isotonic/Hermes-2-Pro-Mixtral-4x7B)

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Note: green Score (e.g. "73.2") means that the model is better than Isotonic/Hermes-2-Pro-Mixtral-4x7B.

Rank the Hermes 2 Pro Mixtral 4x7B 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  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803
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