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Borea Phi 3.5 Mini Instruct Common by AXCXEPT

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Borea Phi 3.5 Mini Instruct Common is an open-source language model by AXCXEPT. Features: 3.8b LLM, VRAM: 7.7GB, Context: 128K, License: mit, Instruction-Based, LLM Explorer Score: 0.15.

  Conversational   Custom code   En   Endpoints compatible   Instruct   Ja   Phi3   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/AXCXEPT/Borea-Phi-3.5-mini-Instruct-Common 

Borea Phi 3.5 Mini Instruct Common Benchmarks

LLME Score: 0.15094
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Borea Phi 3.5 Mini Instruct Common (AXCXEPT/Borea-Phi-3.5-mini-Instruct-Common)
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Borea Phi 3.5 Mini Instruct Common Parameters and Internals

Model Type 
text generation, conversational
Use Cases 
Areas:
research, commercial applications
Additional Notes 
The model is provided for research and development only and should be considered an experimental prototype.
Supported Languages 
ja (high proficiency), en (unknown)
Training Details 
Data Sources:
Japanese Wikipedia, FineWeb
Methodology:
plain instruction tuning
Training Time:
2 hours on H100PCIe × 8
Hardware Used:
H100PCIe × 8
Input Output 
Accepted Modalities:
text
LLM NameBorea Phi 3.5 Mini Instruct Common
Repository 🤗https://huggingface.co/AXCXEPT/Borea-Phi-3.5-mini-Instruct-Common 
Model Size3.8b
Required VRAM7.7 GB
Updated2026-03-05
MaintainerAXCXEPT
Model Typephi3
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   2.7 GB: 2-of-2
Supported Languagesja en
Model ArchitecturePhi3ForCausalLM
Licensemit
Context Length131072
Model Max Length131072
Transformers Version4.43.0
Tokenizer ClassLlamaTokenizer
Padding Token<|endoftext|>
Vocabulary Size32064
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than AXCXEPT/Borea-Phi-3.5-mini-Instruct-Common.

Rank the Borea Phi 3.5 Mini Instruct Common 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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