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NeuralTrix 7B DPO by CultriX

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NeuralTrix 7B DPO is an open-source language model by CultriX. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.12, Arc: 72.3, HellaSwag: 88.9, MMLU: 64.1, GSM8K: 68.

  Aimavenai/aimaven-prometheus Base model:aimavenai/aimaven-p... Base model:flemmingmiguel/mbx-... Base model:merge:aimavenai/aim... Base model:merge:flemmingmigue... Base model:merge:mlabonne/omni... Base model:mlabonne/omnibeagle...   Endpoints compatible   Flemmingmiguel/mbx-7b-v3   Lazymergekit   Merge   Mergekit   Mistral   Mlabonne/omnibeagle-7b   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/CultriX/NeuralTrix-7B-dpo 

NeuralTrix 7B DPO Benchmarks

ARC: 72.27 vs 96.7 (so35)-25.3%
HellaSwag: 88.91 vs 95.3 (gpt4)-6.7%
MMLU: 64.06 vs 88.3 (so35)-27.5%
GSM8K: 68.01 vs 96.4 (so35)-29.5%
LLME Score: 0.12473
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
NeuralTrix 7B DPO (CultriX/NeuralTrix-7B-dpo)
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NeuralTrix 7B DPO Parameters and Internals

Model Type 
text-generation
Training Details 
Data Sources:
https://huggingface.co/datasets/jondurbin/truthy-dpo-v0.1
Methodology:
Trained with DPO using LazyMergekit.
Input Output 
Accepted Modalities:
text
LLM NameNeuralTrix 7B DPO
Repository 🤗https://huggingface.co/CultriX/NeuralTrix-7B-dpo 
Base Model(s)  OmniBeagle 7B   MBX 7B V3   AiMaven Prometheus   mlabonne/OmniBeagle-7B   flemmingmiguel/MBX-7B-v3   AiMavenAi/AiMaven-Prometheus
Model Size7b
Required VRAM14.4 GB
Updated2026-05-11
MaintainerCultriX
Model Typemistral
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than CultriX/NeuralTrix-7B-dpo.

Rank the NeuralTrix 7B DPO 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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