some comparison
#1
by
BJsword
- opened
What are the pros and cons of small parameter models like WuKong compared to large 70+B parameter models?
Small parameter models like WuKong have the advantage of being computationally efficient and require less memory compared to large 70+B parameter models. This means that they can be trained and deployed more quickly, making them suitable for applications with limited computational resources. However, small parameter models may have limited representational power and may not capture complex patterns and nuances as effectively as large parameter models. Therefore, their performance may be inferior in tasks that require a high level of accuracy and understanding.