Qwen2.5-Coder-1.5B-Instruct

Maintained By
Qwen

Qwen2.5-Coder-1.5B-Instruct

PropertyValue
Parameter Count1.54B
Context Length32,768 tokens
LicenseApache 2.0
ArchitectureTransformers with RoPE, SwiGLU, RMSNorm
Research PaperarXiv:2409.12186

What is Qwen2.5-Coder-1.5B-Instruct?

Qwen2.5-Coder-1.5B-Instruct is part of the latest series of Code-Specific Qwen large language models, specifically designed for code generation and reasoning tasks. It represents a significant advancement in the Qwen family, trained on 5.5 trillion tokens including source code and text-code grounding data.

Implementation Details

The model architecture employs sophisticated components including 28 layers and a hybrid attention system with 12 heads for queries and 2 for key-values. It utilizes BF16 precision and implements advanced features like RoPE positional embeddings and SwiGLU activations.

  • Full 32K token context window
  • Efficient architecture with 1.31B non-embedding parameters
  • Optimized for both code generation and general tasks
  • Implements Group Query Attention (GQA)

Core Capabilities

  • Advanced code generation and completion
  • Code reasoning and problem-solving
  • Bug identification and fixing
  • Mathematical computation support
  • Text-code grounding tasks

Frequently Asked Questions

Q: What makes this model unique?

This model stands out for its efficient architecture that balances size and performance, offering professional-grade coding capabilities in a relatively compact 1.5B parameter package. It's particularly notable for its extensive 32K context window and specialized training on code-specific tasks.

Q: What are the recommended use cases?

The model excels in code generation, debugging, and technical documentation tasks. It's particularly well-suited for developers needing AI assistance in coding projects, code review processes, and educational programming contexts.

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