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NebulaNet V2 4x7B MoE by davideuler

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  Autotrain compatible Base model:contextualai/contex... Base model:quantized:contextua...   Coding   Conversational   Endpoints compatible   Gguf   Mixtral   Moe   Multilingual   Quantized   Region:us   Safetensors

NebulaNet V2 4x7B MoE Benchmarks

LLME Score: 0.20108
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

NebulaNet V2 4x7B MoE Parameters and Internals

LLM NameNebulaNet V2 4x7B MoE
Repository 🤗https://huggingface.co/davideuler/NebulaNet-v2-4x7B-moe 
Base Model(s)  Contextual KTO Mistral PairRM   ContextualAI/Contextual_KTO_Mistral_PairRM
Required VRAM8.8 GB
Updated2024-10-18
Maintainerdavideuler
Model Typemixtral
Model Files  8.8 GB   19.8 GB   25.7 GB
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureMixtralForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.39.1
Tokenizer ClassLlamaTokenizer
Padding Token<s>
Vocabulary Size32000
Torch Data Typebfloat16
NebulaNet V2 4x7B MoE (davideuler/NebulaNet-v2-4x7B-moe)

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WizardLM 2 8x22 EXL2 4.0bpw64K / 70.9 GB51
Note: green Score (e.g. "73.2") means that the model is better than davideuler/NebulaNet-v2-4x7B-moe.

Rank the NebulaNet V2 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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