Viper-Coder-Hybrid-v1.3
| Property | Value |
|---|---|
| Base Architecture | Qwen 2.5 14B |
| Parameter Count | 14 Billion |
| Context Length | 128K tokens |
| Output Length | 8K tokens |
| Model URL | Hugging Face |
What is Viper-Coder-Hybrid-v1.3?
Viper-Coder-Hybrid-v1.3 is an advanced language model specifically optimized for coding and technical tasks. Built on the Qwen 2.5 14B architecture, it has been fine-tuned on synthetic datasets focusing on coding logits and chain-of-thought reasoning. The model excels in code generation, debugging, and complex problem-solving across multiple programming languages.
Implementation Details
The model leverages transformer architecture with significant improvements in context understanding and structured data processing. It supports up to 128K tokens for input and can generate responses up to 8K tokens, making it suitable for extensive coding tasks and documentation generation.
- Built on Qwen 2.5 14B architecture with specialized fine-tuning
- Supports 29+ programming languages including Python, JavaScript, C++, Java, SQL
- Enhanced chain-of-thought reasoning capabilities
- Optimized for structured output formats (JSON, YAML)
Core Capabilities
- Advanced code generation and debugging across multiple languages
- Complex algorithmic reasoning and problem-solving
- Technical documentation generation
- Mathematical and scientific computation support
- Structured data processing and pipeline automation
Frequently Asked Questions
Q: What makes this model unique?
The model's specialized fine-tuning for coding tasks, combined with its extensive context window of 128K tokens and advanced reasoning capabilities, makes it particularly effective for complex programming and technical tasks. Its performance on the Open LLM Leaderboard shows strong results in instruction following (75.55%) and mathematical reasoning.
Q: What are the recommended use cases?
The model excels in code generation, debugging, algorithm development, technical documentation writing, and complex problem-solving tasks. It's particularly well-suited for professional developers, technical writers, and researchers working on complex programming projects.
