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NeuTrixOmniBe 7B Model Remix by Kukedlc

 »  All LLMs  »  Kukedlc  »  NeuTrixOmniBe 7B Model Remix   URL Share it on

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  Merged Model   Autotrain compatible Base model:cultrix/neuraltrix-... Base model:paulml/omnibeaglesq...   Cultrix/neuraltrix-7b-dpo   Endpoints compatible   Mistral   Model-index Paulml/omnibeaglesquaredmbx-v3...   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Kukedlc/NeuTrixOmniBe-7B-model-remix 

NeuTrixOmniBe 7B Model Remix Benchmarks

ARC: 72.61 vs 96.7 (so35)-24.9%
HellaSwag: 89.07 vs 95.3 (gpt4)-6.5%
MMLU: 64.63 vs 88.3 (so35)-26.8%
TruthfulQA: 76.91 vs 59 (gpt4)30.4%
WinoGrande: 85.08 vs 87.5 (gpt4)-2.8%
GSM8K: 69.14 vs 96.4 (so35)-28.3%
LLME Score: 0.18136
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
NeuTrixOmniBe 7B Model Remix (Kukedlc/NeuTrixOmniBe-7B-model-remix)

NeuTrixOmniBe 7B Model Remix Parameters and Internals

Model Type 
text-generation
Additional Notes 
Model is created using LazyMergekit and merges CultriX/NeuralTrix-7B-dpo and paulml/OmniBeagleSquaredMBX-v3-7B-v2 models.
LLM NameNeuTrixOmniBe 7B Model Remix
Repository 🤗https://huggingface.co/Kukedlc/NeuTrixOmniBe-7B-model-remix 
Base Model(s)  NeuralTrix 7B DPO   OmniBeagleSquaredMBX V3 7B V2   CultriX/NeuralTrix-7B-dpo   paulml/OmniBeagleSquaredMBX-v3-7B-v2
Merged ModelYes
Model Size7b
Required VRAM14.4 GB
Updated2024-12-22
MaintainerKukedlc
Model Typemistral
Model Files  1.9 GB: 1-of-8   2.0 GB: 2-of-8   1.9 GB: 3-of-8   2.0 GB: 4-of-8   1.8 GB: 5-of-8   1.9 GB: 6-of-8   2.0 GB: 7-of-8   0.9 GB: 8-of-8
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than Kukedlc/NeuTrixOmniBe-7B-model-remix.

Rank the NeuTrixOmniBe 7B Model Remix Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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 v20241217
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