WizardCoder-15B-V1.0
| Property | Value |
|---|---|
| License | OpenRAIL-M |
| HumanEval Score | 57.3 pass@1 |
| Paper | WizardCoder Paper |
| Base Model | StarCoder |
What is WizardCoder-15B-V1.0?
WizardCoder-15B-V1.0 is a powerful code language model that represents a significant advancement in AI-powered code generation. Built upon StarCoder and fine-tuned with 78k evolved coding instructions, it achieves remarkable performance of 57.3% pass@1 on the HumanEval benchmark, surpassing many open-source alternatives by a significant margin.
Implementation Details
The model was fine-tuned using specific hyperparameters including a batch size of 512, learning rate of 2e-5, and 3 epochs of training. It employs cosine learning rate scheduling and supports a maximum sequence length of 2048 tokens.
- Uses modified Evol-Instruct method specifically adapted for coding tasks
- Trained on carefully curated code-specific instruction dataset
- Implements greedy decoding for code generation
- Supports multiple programming languages with focus on Python
Core Capabilities
- Strong performance on code generation tasks (57.3% pass@1 on HumanEval)
- Surpasses many closed-source models including Claude-Plus and Bard
- Handles complex coding instructions and problem-solving tasks
- Efficient inference with support for batch processing
Frequently Asked Questions
Q: What makes this model unique?
WizardCoder's uniqueness lies in its evolved instruction tuning approach specifically designed for code generation, achieving state-of-the-art performance among open-source code LLMs while maintaining a relatively compact model size of 15B parameters.
Q: What are the recommended use cases?
The model excels at code generation, problem-solving, and handling complex programming tasks. It's particularly well-suited for Python programming but can handle multiple programming languages. It's ideal for developers looking for an open-source solution for code generation and assistance.
