WizardCoder-Python-34B-V1.0-GPTQ
| Property | Value |
|---|---|
| Base Model | WizardLM/WizardCoder-Python-34B-V1.0 |
| Parameter Count | 34 Billion |
| Quantization | 4-bit GPTQ |
| License | Llama 2 |
| HumanEval Score | 73.2% pass@1 |
What is WizardCoder-Python-34B-V1.0-GPTQ?
WizardCoder-Python-34B-V1.0-GPTQ is a quantized version of the powerful WizardCoder model, specifically optimized for Python programming tasks. This model represents a significant advancement in code generation capabilities, achieving state-of-the-art performance that surpasses even GPT-4's early 2023 results on the HumanEval benchmark.
Implementation Details
The model has been quantized using GPTQ technology to reduce its size while maintaining performance. It's available in multiple quantization options, including 4-bit versions with different group sizes (32g, 64g, 128g) and a 3-bit version for more efficient deployment.
- Multiple GPTQ quantization options for different hardware requirements
- Optimized for 4-bit inference with ExLlama compatibility
- Uses the Evol-Instruct-Code dataset for training
- Sequence length of 8192 tokens
Core Capabilities
- State-of-the-art Python code generation
- 73.2% pass@1 on HumanEval benchmark
- Superior performance compared to ChatGPT-3.5 and Claude2
- Efficient memory usage through quantization
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its exceptional performance in Python code generation while being optimized for efficient deployment through quantization. It achieves higher accuracy than many leading commercial models while being openly available.
Q: What are the recommended use cases?
The model excels at Python programming tasks, including code generation, debugging, and optimization. It's particularly suitable for professional developers and organizations requiring high-quality code generation while working with limited computational resources.
