WizardCoder-33B-V1.1
| Property | Value |
|---|---|
| Parameter Count | 33.3B |
| Model Type | Code Generation LLM |
| License | MSFTResearch |
| Paper | WizardCoder Paper |
What is WizardCoder-33B-V1.1?
WizardCoder-33B-V1.1 is a state-of-the-art open-source code language model trained on the deepseek-coder-33b-base architecture. Released in January 2024, it achieves remarkable performance metrics, including 79.9% pass@1 on HumanEval and 73.2% on HumanEval-Plus, surpassing both ChatGPT 3.5 and Gemini Pro.
Implementation Details
The model was developed using the Code Evol-Instruct methodology applied to Code-Alpaca data, with rigorous data contamination checks and deduplication methods to prevent test set leakage. It utilizes BF16 precision and requires specific system prompts for optimal performance.
- Built on transformers architecture with 33.3B parameters
- Implements specialized Code Evol-Instruct training methodology
- Supports text-generation-inference endpoints
- Requires specific formatting for system prompts
Core Capabilities
- 79.9% pass@1 on HumanEval benchmark
- 73.2% pass@1 on HumanEval-Plus
- 78.9% pass@1 on MBPP benchmark
- 66.9% pass@1 on MBPP-Plus
- Outperforms major commercial models in code generation tasks
Frequently Asked Questions
Q: What makes this model unique?
WizardCoder-33B-V1.1 stands out for its superior performance on code generation benchmarks, outperforming both open-source and commercial alternatives like ChatGPT 3.5 and Gemini Pro. Its unique Code Evol-Instruct training methodology and careful data contamination prevention contribute to its exceptional capabilities.
Q: What are the recommended use cases?
The model excels in code generation tasks, making it ideal for automated programming assistance, code completion, and software development support. It's particularly effective for Python programming tasks, as demonstrated by its high performance on standard benchmarks.
