WizardLM-2-8x22B
| Property | Value |
|---|---|
| Parameter Count | 141B |
| Model Type | Mixture of Experts (MoE) |
| Base Model | Mixtral-8x22B-v0.1 |
| License | Apache 2.0 |
| Developer | WizardLM@Microsoft AI |
What is WizardLM-2-8x22B?
WizardLM-2-8x22B is a state-of-the-art large language model that represents Microsoft's most advanced offering in the WizardLM series. Built on the Mixtral-8x22B architecture, this model employs a Mixture of Experts (MoE) approach with 141B parameters, delivering exceptional performance across complex chat, multilingual tasks, reasoning, and agent-based interactions.
Implementation Details
The model implements a fully AI-powered synthetic training system and follows the Vicuna prompt format for multi-turn conversations. It's trained using BF16 precision and demonstrates remarkable capabilities in various benchmark tests, including achieving 52.72% accuracy on IFEval and 48.58% on BBH (3-Shot) evaluations.
- Supports multi-turn conversations with Vicuna-style prompting
- Implements advanced MoE architecture for efficient processing
- Utilizes BF16 tensor type for optimal performance
- Built with Apache 2.0 license for open usage
Core Capabilities
- Achieves competitive performance against leading proprietary models on MT-Bench
- Excels in complex instruction following with strong win rates against GPT-4 models
- Demonstrates superior performance in multilingual tasks
- Shows strong reasoning capabilities across various domains
- Achieves 39.96% accuracy on MMLU-PRO (5-shot)
Frequently Asked Questions
Q: What makes this model unique?
WizardLM-2-8x22B stands out for its impressive performance metrics that rival proprietary models while maintaining open-source accessibility. Its MoE architecture and comprehensive training system enable superior performance across diverse tasks.
Q: What are the recommended use cases?
The model excels in complex chat applications, multilingual processing, advanced reasoning tasks, and agent-based interactions. It's particularly well-suited for applications requiring sophisticated language understanding and generation capabilities.
