MixTAO-7Bx2-MoE-v8.1
| Property | Value |
|---|---|
| Parameter Count | 12.9B |
| Model Type | Mixture of Experts (MoE) |
| License | Apache 2.0 |
| Tensor Type | BF16 |
What is MixTAO-7Bx2-MoE-v8.1?
MixTAO-7Bx2-MoE-v8.1 is an advanced Mixture of Experts (MoE) language model designed for experimental research in large language model technology. With 12.9B parameters, it demonstrates impressive performance across multiple benchmarks, achieving an average score of 77.50 on the Open LLM Leaderboard.
Implementation Details
The model utilizes a BF16 tensor format and implements the Mixture of Experts architecture, allowing for efficient parameter usage and specialized processing across different types of inputs. It follows the Alpaca prompt template format for consistency in interactions.
- Achieves 89.22% accuracy on HellaSwag (10-Shot)
- Scores 71.11% on GSM8k mathematical reasoning (5-shot)
- Demonstrates 78.57% accuracy on TruthfulQA (0-shot)
- MMLU performance of 64.92% (5-Shot)
Core Capabilities
- Strong performance in reasoning tasks (AI2 Reasoning Challenge: 73.81%)
- Excellent common sense understanding (Winogrande: 87.37%)
- Robust mathematical problem-solving abilities
- Zero-shot and few-shot learning capabilities
Frequently Asked Questions
Q: What makes this model unique?
The model's Mixture of Experts architecture allows for specialized processing of different types of inputs, making it particularly effective across a diverse range of tasks while maintaining efficiency in parameter usage.
Q: What are the recommended use cases?
This model is primarily designed for research and experimentation in large language model technology. It excels in reasoning tasks, mathematical problem-solving, and common sense understanding, making it suitable for academic and research applications.
