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MBX 7B V3 DPO by macadeliccc

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  Autotrain compatible Dataset:jondurbin/truthy-dpo-v...   Endpoints compatible   Mistral   Model-index   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/macadeliccc/MBX-7B-v3-DPO 

MBX 7B V3 DPO Benchmarks

ARC: 73.55 vs 96.7 (so35)-23.9%
HellaSwag: 89.11 vs 95.3 (gpt4)-6.5%
MMLU: 64.91 vs 88.3 (so35)-26.5%
TruthfulQA: 74 vs 59 (gpt4)25.4%
WinoGrande: 85.56 vs 87.5 (gpt4)-2.2%
GSM8K: 69.67 vs 96.4 (so35)-27.7%
LLME Score: 0.18126
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MBX 7B V3 DPO (macadeliccc/MBX-7B-v3-DPO)

MBX 7B V3 DPO Parameters and Internals

Model Type 
text-generation
Training Details 
Data Sources:
jondurbin/truthy-dpo-v0.1
LLM NameMBX 7B V3 DPO
Repository 🤗https://huggingface.co/macadeliccc/MBX-7B-v3-DPO 
Model Size7b
Required VRAM14.4 GB
Updated2024-12-21
Maintainermacadeliccc
Model Typemistral
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Model ArchitectureMistralForCausalLM
Licensecc
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 macadeliccc/MBX-7B-v3-DPO.

Rank the MBX 7B V3 DPO 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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Release v20241217
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