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Phi 4 RR Shoup by bunnycore

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Phi 4 RR Shoup is an open-source language model by bunnycore. Features: 14.7b LLM, VRAM: 29.5GB, Context: 16K, LLM Explorer Score: 0.29.

  Arxiv:2203.05482   Autotrain compatible Base model:bunnycore/phi-4-mod... Base model:bunnycore/phi-4-rea... Base model:merge:bunnycore/phi... Base model:merge:bunnycore/phi... Base model:merge:quazim0t0/phi... Base model:quazim0t0/phi4.turn...   Conversational   Endpoints compatible   Llama   Merge   Mergekit   Model-index   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/bunnycore/Phi-4-RR-Shoup 

Phi 4 RR Shoup Benchmarks

LLME Score: 0.29161
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Phi 4 RR Shoup (bunnycore/Phi-4-RR-Shoup)
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Phi 4 RR Shoup Parameters and Internals

LLM NamePhi 4 RR Shoup
Repository 🤗https://huggingface.co/bunnycore/Phi-4-RR-Shoup 
Base Model(s)  Quazim0t0/Phi4.Turn.R1Distill_v1.5.1-Tensors   Phi 4 ReasoningRP   Phi 4 Model Stock V4   Quazim0t0/Phi4.Turn.R1Distill_v1.5.1-Tensors   bunnycore/Phi-4-ReasoningRP   bunnycore/Phi-4-Model-Stock-v4
Model Size14.7b
Required VRAM29.5 GB
Updated2025-09-23
Maintainerbunnycore
Model Typellama
Model Files  5.0 GB: 1-of-6   5.0 GB: 2-of-6   5.0 GB: 3-of-6   4.9 GB: 4-of-6   5.0 GB: 5-of-6   4.6 GB: 6-of-6
Model ArchitectureLlamaForCausalLM
Context Length16384
Model Max Length16384
Transformers Version4.48.2
Tokenizer ClassGPT2Tokenizer
Padding Token<|dummy_87|>
Vocabulary Size100352
Torch Data Typebfloat16

Best Alternatives to Phi 4 RR Shoup

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Context / RAM
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E2 Phi4 Instruct NTK Scaled31K / 29.4 GB200
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Phi 416K / 29.4 GB2552290
Luminis Phi 416K / 29.5 GB110913
Orca Mini Phi 416K / 29.4 GB8858
Phi 4 Sce Exp V0.116K / 29.5 GB31
Phi 4 Model Stock V416K / 29.5 GB189
Phi 4 RStock V0.116K / 29.5 GB180
Note: green Score (e.g. "73.2") means that the model is better than bunnycore/Phi-4-RR-Shoup.

Rank the Phi 4 RR Shoup 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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