Viper-Coder-v1.6-r999
| Property | Value |
|---|---|
| Base Architecture | Qwen 2.5 14B |
| Parameter Count | 14 Billion |
| Context Window | 128K tokens |
| Model Type | Causal Language Model |
| Hugging Face | Link |
What is Viper-Coder-v1.6-r999?
Viper-Coder-v1.6-r999 is a specialized large language model optimized for coding and technical reasoning tasks. Built on the Qwen 2.5 14B architecture, it has been extensively fine-tuned on synthetic datasets focusing on coding logits and chain-of-thought reasoning. The model demonstrates exceptional capabilities in code generation, debugging, and technical problem-solving across multiple programming languages.
Implementation Details
The model leverages state-of-the-art training techniques with significant improvements in context understanding and structured data processing. It can handle up to 128K tokens of context and generate responses up to 8K tokens, making it suitable for complex coding projects and extended technical documentation.
- Advanced fine-tuning on specialized coding datasets
- Optimized for chain-of-thought reasoning and logical problem-solving
- Support for 29+ programming languages
- Enhanced instruction-following capabilities
Core Capabilities
- Elite-level code generation and debugging across multiple languages
- Complex algorithmic reasoning and mathematical computation
- Structured data processing (JSON, XML, SQL)
- Technical documentation generation
- Multi-step problem-solving with improved theorem proving
Frequently Asked Questions
Q: What makes this model unique?
The model's specialized focus on coding tasks, combined with its large context window of 128K tokens and advanced chain-of-thought reasoning capabilities, sets it apart from general-purpose LLMs. Its performance on coding benchmarks, particularly in MATH Lvl 5 (56.57%) and BBH 3-shot (49.27%), demonstrates its superior technical reasoning abilities.
Q: What are the recommended use cases?
The model excels in code generation, debugging, algorithm development, and technical content creation. It's particularly suitable for professional developers, technical writers, and researchers working on complex programming projects or technical documentation.
