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Borea Phi 3.5 Mini Instruct Coding by AXCXEPT

 »  All LLMs  »  AXCXEPT  »  Borea Phi 3.5 Mini Instruct Coding   URL Share it on

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  Autotrain compatible   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-Coding 

Borea Phi 3.5 Mini Instruct Coding Benchmarks

LLME Score: 0.22239
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 Coding (AXCXEPT/Borea-Phi-3.5-mini-Instruct-Coding)

Borea Phi 3.5 Mini Instruct Coding Parameters and Internals

Model Type 
text generation, conversational
Use Cases 
Areas:
research, general applications
Primary Use Cases:
Coding, Extraction in Japanese language
Additional Notes 
This model is experimental and intended for research purposes.
Supported Languages 
ja (High proficiency), en (Unsure, but present)
Training Details 
Data Sources:
Japanese Wikipedia, FineWeb
Methodology:
Plain instruction tuning method
Hardware Used:
H100PCIe × 8
Input Output 
Accepted Modalities:
text
LLM NameBorea Phi 3.5 Mini Instruct Coding
Repository 🤗https://huggingface.co/AXCXEPT/Borea-Phi-3.5-mini-Instruct-Coding 
Model Size3.8b
Required VRAM7.7 GB
Updated2025-01-23
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-Coding.

Rank the Borea Phi 3.5 Mini Instruct Coding 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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