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Microsoft/Phi-4

Phi-4 is Microsoft's latest large language model in the Phi series, featuring advanced reasoning capabilities and improved performance across various tasks while maintaining computational efficiency.

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Model Information

Model
Phi-4
Author
Microsoft
Parameters
Architecture
transformer-based
Format
GGUF
Size on disk
8.10 GB
Quantization
License

./README.md

Phi-4

Phi-4 is the latest addition to Microsoft's Phi model series, representing a significant advancement in compact yet powerful language models. Building upon the success of its predecessors (Phi-1, Phi-1.5, and Phi-2), Phi-4 demonstrates enhanced capabilities in reasoning, coding, and general language understanding.

Model Variants

  • Phi-4-Base: The foundation model with core language understanding capabilities
  • Phi-4-Chat: Optimized variant for conversational applications
  • Phi-4-Code: Specialized version for programming and code generation
  • Phi-4-Math: Enhanced variant for mathematical reasoning and problem-solving

Key Features

  • Advanced Reasoning: Improved performance on complex logical and analytical tasks
  • Code Generation: Enhanced capabilities in understanding and generating code across multiple programming languages
  • Efficient Architecture: Optimized model design for better performance with reasonable computational requirements
  • Context Understanding: Better grasp of context and improved coherence in responses
  • Safety Aligned: Built-in safety measures and content filtering capabilities

Technical Specifications

  • Architecture: Transformer-based with architectural improvements
  • Parameters: [Size to be confirmed]
  • Context Window: Extended context length for processing longer sequences
  • Training Data: Curated dataset including:
    • High-quality text from various sources
    • Code repositories
    • Mathematical and scientific content
    • Educational materials

Performance Highlights

  • Superior performance in coding tasks compared to previous Phi models
  • Enhanced mathematical reasoning capabilities
  • Improved natural language understanding and generation
  • Better handling of complex instructions and multi-step tasks

Use Cases

  • Software Development and Code Generation
  • Educational Applications
  • Research and Academic Writing
  • Technical Documentation
  • Mathematical Problem Solving
  • General Language Tasks

Additional Resources

Community and Support