DeepSeek Coder 33B Base
| Property | Value |
|---|---|
| Parameter Count | 33.3B |
| Training Data | 2T tokens (87% code, 13% language) |
| Context Window | 16K tokens |
| License | DeepSeek License |
| Tensor Type | BF16 |
What is deepseek-coder-33b-base?
DeepSeek Coder 33B Base is a state-of-the-art code generation model trained from scratch on an extensive dataset of 2 trillion tokens. It represents the largest variant in the DeepSeek Coder family, designed specifically for advanced code completion, generation, and understanding tasks across multiple programming languages.
Implementation Details
The model utilizes Grouped-Query Attention architecture and is implemented using PyTorch with Safetensors support. It features a substantial 16K token context window, enabling it to understand and process large code segments at the project level.
- Trained on a diverse dataset comprising 87% code and 13% natural language content
- Implements fill-in-the-blank task capability for code infilling
- Supports both English and Chinese language interactions
- Utilizes advanced transformer architecture with BF16 precision
Core Capabilities
- Project-level code completion with extended context understanding
- Advanced code infilling and insertion capabilities
- Multi-language programming support with state-of-the-art performance
- Benchmark-leading results on HumanEval, MultiPL-E, MBPP, DS-1000, and APPS
Frequently Asked Questions
Q: What makes this model unique?
The combination of its massive scale (33B parameters), extensive training data (2T tokens), and specialized architecture for code understanding makes it particularly powerful for development tasks. The 16K context window and fill-in-the-blank capabilities set it apart from other code models.
Q: What are the recommended use cases?
The model excels at project-level code completion, complex code generation, and understanding tasks. It's particularly suitable for professional developers requiring sophisticated code assistance across multiple programming languages and large codebases.
