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PhigRange DPO by johnsnowlabs

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  Autotrain compatible   Chatml Dataset:mlabonne/chatml-openhe...   Distillation   Dpo   En   Endpoints compatible   Finetuned   Generated from trainer   Gpt4   Instruct   Phi   Region:us   Safetensors   Sharded   Synthetic data   Tensorflow
Model Card on HF 🤗: https://huggingface.co/johnsnowlabs/PhigRange-DPO 

PhigRange DPO Benchmarks

ARC: 25.77 vs 96.7 (so35)-73.4%
HellaSwag: 25.7 vs 95.3 (gpt4)-73%
MMLU: 25.52 vs 88.3 (so35)-71.1%
TruthfulQA: 47.98 vs 59 (gpt4)-18.7%
WinoGrande: 50.28 vs 87.5 (gpt4)-42.5%
LLME Score: 0.20959
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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PhigRange DPO Parameters and Internals

Model Type 
text-generation
Supported Languages 
en (high)
Training Details 
Data Sources:
mlabonne/chatml-OpenHermes2.5-dpo-binarized-alpha
Methodology:
DPO fine-tuning
LLM NamePhigRange DPO
Repository 🤗https://huggingface.co/johnsnowlabs/PhigRange-DPO 
Base Model(s)  PhigRange-2.7B-slerp   /PhigRange-2.7B-slerp
Model Size2.7b
Required VRAM5.6 GB
Updated2025-06-09
Maintainerjohnsnowlabs
Model Typephi
Model Files  5.0 GB: 1-of-2   0.6 GB: 2-of-2
Supported Languagesen
Model ArchitecturePhiForCausalLM
Licensecc-by-nc-4.0
Context Length2048
Model Max Length2048
Transformers Version4.40.0.dev0
Tokenizer ClassCodeGenTokenizer
Vocabulary Size51200
Torch Data Typefloat16
PhigRange DPO (johnsnowlabs/PhigRange-DPO)

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Rank the PhigRange 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 v20241124
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