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Phi 2.7B MERGED by ayoubkirouane

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Phi 2.7B MERGED is an open-source language model by ayoubkirouane. Features: 2.7b LLM, VRAM: 5.6GB, License: apache-2.0, Merged, LLM Explorer Score: 0.11.

  Merged Model   Ar Base model:rhysjones/phi-2-ora... Base model:yhyu13/phi-2-sft-dp...   Custom code   En   Endpoints compatible   Fr   Phi-msft   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/ayoubkirouane/Phi-2.7B_MERGED 

Phi 2.7B MERGED Benchmarks

LLME Score: 0.11347
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Phi 2.7B MERGED (ayoubkirouane/Phi-2.7B_MERGED)
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Phi 2.7B MERGED Parameters and Internals

Model Type 
text generation
Additional Notes 
The model is derived from merging rhysjones/phi-2-orange and Yhyu13/phi-2-sft-dpo-gpt4_en-ep1 using the SLERP merge method.
Supported Languages 
en (high), fr (medium), ar (medium)
LLM NamePhi 2.7B MERGED
Repository 🤗https://huggingface.co/ayoubkirouane/Phi-2.7B_MERGED 
Base Model(s)  Phi 2 Orange   Phi 2 Sft DPO Gpt4 En Ep1   rhysjones/phi-2-orange   Yhyu13/phi-2-sft-dpo-gpt4_en-ep1
Merged ModelYes
Model Size2.7b
Required VRAM5.6 GB
Updated2026-04-26
Maintainerayoubkirouane
Model Typephi-msft
Model Files  5.6 GB: 1-of-1
Supported Languagesen ar fr
Model ArchitecturePhiForCausalLM
Licenseapache-2.0
Model Max Length2048
Transformers Version4.36.2
Tokenizer ClassCodeGenTokenizer
Padding Token<|endoftext|>
Vocabulary Size51200
Torch Data Typebfloat16
Activation Functiongelu_new

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Note: green Score (e.g. "73.2") means that the model is better than ayoubkirouane/Phi-2.7B_MERGED.

Rank the Phi 2.7B MERGED 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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