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AdaptLLM 4x7B MoE by Isotonic

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AdaptLLM 4x7B MoE Benchmarks

LLME Score: 0.18626
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

AdaptLLM 4x7B MoE Parameters and Internals

LLM NameAdaptLLM 4x7B MoE
Repository 🤗https://huggingface.co/Isotonic/AdaptLLM-4x7B-MoE 
Model Size20.2b
Required VRAM39.8 GB
Updated2024-10-08
MaintainerIsotonic
Model Typemixtral
Instruction-BasedYes
Model Files  2.0 GB: 1-of-21   1.9 GB: 2-of-21   1.9 GB: 3-of-21   1.9 GB: 4-of-21   1.9 GB: 5-of-21   1.9 GB: 6-of-21   1.9 GB: 7-of-21   1.9 GB: 8-of-21   1.9 GB: 9-of-21   1.9 GB: 10-of-21   1.9 GB: 11-of-21   1.9 GB: 12-of-21   1.9 GB: 13-of-21   1.9 GB: 14-of-21   1.9 GB: 15-of-21   1.9 GB: 16-of-21   1.9 GB: 17-of-21   1.9 GB: 18-of-21   1.9 GB: 19-of-21   2.0 GB: 20-of-21   1.6 GB: 21-of-21
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.2
Tokenizer ClassLlamaTokenizer
Padding Token<s>
Vocabulary Size32000
Torch Data Typefloat16
AdaptLLM 4x7B MoE (Isotonic/AdaptLLM-4x7B-MoE)

Rank the AdaptLLM 4x7B MoE 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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