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Phi3 Mini Math by jrc

 »  All LLMs  »  jrc  »  Phi3 Mini Math   URL Share it on

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  Autotrain compatible   Conversational   Custom code   Dataset:tiger-lab/math-plus   En   Endpoints compatible   Instruct   Minerva-math   Phi3   Region:us   Torchtune
Model Card on HF 🤗: https://huggingface.co/jrc/phi3-mini-math 

Phi3 Mini Math Benchmarks

LLME Score: 0.18738
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Phi3 Mini Math (jrc/phi3-mini-math)

Phi3 Mini Math Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Research, Education
Applications:
Math tutoring, Solving math problems
Primary Use Cases:
Answering math questions, Math problem solving
Supported Languages 
en (high)
Training Details 
Data Sources:
TIGER-Lab/MATH-plus
Data Volume:
894k samples
Methodology:
Finetuned using torchtune
Training Time:
10 hours
Hardware Used:
4 x NVIDIA A100 GPUs
Input Output 
Input Format:
Text input
Accepted Modalities:
text
Output Format:
Text output
LLM NamePhi3 Mini Math
Repository 🤗https://huggingface.co/jrc/phi3-mini-math 
Required VRAM2.7 GB
Updated2025-02-22
Maintainerjrc
Model Typephi3
Instruction-BasedYes
Model Files  0.0 GB   5.0 GB: 1-of-2   2.7 GB: 2-of-2
Supported Languagesen
Model ArchitecturePhi3ForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.39.3
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 jrc/phi3-mini-math.

Rank the Phi3 Mini Math 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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Release v20241227
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