| Property | Value |
|---|---|
| License | BigCode OpenRAIL-M |
| Architecture | Transformer-based |
| Best Performance | 57.3 pass@1 on HumanEval |
| Format | GGML Quantized |
What is WizardCoder-15B-1.0-GGML?
WizardCoder-15B-1.0-GGML is a specialized code generation model that has been optimized and quantized for efficient deployment. Built on the StarCoder architecture and enhanced through the Evol-Instruct method, it represents a significant advancement in open-source code generation capabilities.
Implementation Details
The model comes in various quantization levels (4-bit to 8-bit) to balance performance and resource usage. The q4_0 variant requires 13.25GB RAM while offering good performance, while the q8_0 variant needs 22.61GB RAM but provides near float16 quality.
- Multiple quantization options (q4_0, q4_1, q5_0, q5_1, q8_0)
- Optimized for use with KoboldCpp and ctransformers
- Requires specific prompt template for optimal performance
- Compatible with several inference engines including GPT4All-UI
Core Capabilities
- Achieves 57.3 pass@1 on HumanEval benchmarks
- Outperforms many closed-source models including Claude-Plus
- Specialized in code-related instruction following
- Supports various programming languages and coding tasks
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its exceptional performance on code generation tasks, achieving state-of-the-art results among open-source models while being optimized for efficient deployment through GGML quantization.
Q: What are the recommended use cases?
The model excels at code generation, code completion, and solving programming problems. It's particularly well-suited for development environments where efficient resource usage is important, thanks to its various quantization options.