64K
0.00126
0.00126
141B
Language

WizardLM 2-8 (22B)

Discover Microsoft’s WizardLM 2-8 (22B), an advanced language model optimized for multilingual conversations and complex reasoning tasks with high efficiency.
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WizardLM 2-8 (22B)

WizardLM 2-8 (22B) is a powerful language model designed for efficient multilingual interactions and complex reasoning tasks.

Model Overview Card for WizardLM 2-8 (22B)

Basic Information

  • Model Name: WizardLM 2-8 (22B)
  • Developer/Creator: Microsoft
  • Release Date: April 2024
  • Version: 2.0
  • Model Type: Large Language Model (LLM)

Description

Overview:

WizardLM 2-8 (22B) is a state-of-the-art large language model developed by Microsoft, designed to excel in complex tasks such as multilingual conversations, reasoning, and agent-based interactions. With its advanced architecture and extensive training, it aims to provide high-quality, contextually relevant responses across various applications.Key Features:

  • 141 Billion Parameters: Offers robust performance for understanding and generating human-like text.
  • Mixture of Experts (MoE) Architecture: Utilizes a combination of specialized models to optimize efficiency and performance.
  • Multilingual Support: Capable of engaging in conversations across multiple languages.
  • High Efficiency: Achieves competitive performance while being significantly faster than larger models.
  • Synthetic Training Data: Trained using a fully AI-powered synthetic training system to enhance learning capabilities.
Intended Use:

The model is intended for software developers and researchers looking to implement advanced natural language processing (NLP) capabilities in applications such as chatbots, virtual assistants, content generation tools, and more.Language Support:WizardLM-2 supports multiple languages, making it suitable for global applications in diverse linguistic contexts.

Technical Details

Architecture:

WizardLM 2-8 (22B) employs a Mixture of Experts architecture that allows the model to activate different subsets of its parameters based on the input, enhancing both speed and performance. This architecture is particularly effective for handling complex reasoning tasks and maintaining high contextual relevance.

Training Data:

The model was trained on a vast dataset consisting of synthetic data generated by AI systems, which allows it to learn quickly from diverse scenarios.

  • Data Source and Size: The training dataset includes a wide range of topics and linguistic styles to ensure robustness and versatility in responses.
  • Diversity and Bias: The training data was curated to minimize biases while maximizing the diversity of inputs, although the reliance on synthetic data raises questions about real-world applicability.
Performance Metrics and Comparison to Other Models:

WizardLM-2 has demonstrated impressive performance metrics:

Usage

Code Samples

The model is available on the AI/ML API platform as "WizardLM 2-8 (22B)" .

API Documentation

Detailed API Documentation is available here.

Ethical Guidelines

Microsoft emphasizes ethical considerations in AI development by promoting transparency regarding the model's capabilities and limitations. The company encourages responsible usage to prevent misuse or harmful applications of generated content. Notably, the initial release was retracted for toxicity testing, highlighting their commitment to ethical standards.

Licensing

WizardLM models are available under an open-source license that allows both research and commercial usage rights while ensuring compliance with ethical standards.

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