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Hermes 2 Pro Mixtral 4x7B by Isotonic

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Hermes 2 Pro Mixtral 4x7B Benchmarks

ARC: 64.25-33.3%
HellaSwag: 82.7-13.2%
MMLU: 62.26-28%
TruthfulQA: 59.020%
WinoGrande: 75.45-13.8%
GSM8K: 60.42-34.3%
nn.n% — How the model compares to the GPT-4.

Hermes 2 Pro Mixtral 4x7B Parameters and Internals

LLM NameHermes 2 Pro Mixtral 4x7B
RepositoryOpen on 🤗 
Model Size24.2b
Required VRAM48.3 GB
Updated2024-07-27
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)

Best Alternatives to Hermes 2 Pro Mixtral 4x7B

Best Alternatives
HF Rank
Context/RAM
Downloads
Likes
Beyonder 4x7B V30.332K / 48.3 GB385956
NeuralStar FusionWriter 4x7b0.332K / 48.3 GB70
Dzakwan MoE 4x7b Beta0.332K / 48.4 GB20590
Mera Mix 4x7B0.332K / 48.3 GB443417
Mixtral 4x7b Slerp0.332K / 96.8 GB2371
CognitiveFusion2 4x7B BF160.332K / 48.3 GB44903
...erges MoE 4x7b V10 Mixtralv0.30.332K / 48.3 GB2420
NeuralMona MoE 4x7B0.332K / 48.3 GB39170
Calme 4x7B MoE V0.10.332K / 48.3 GB34222
Calme 4x7B MoE V0.20.332K / 48.3 GB33102
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  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072501
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