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cloud.google.com·6h ago
AI Research
arXiv CS.AI·Aug 11·5 min read
Shape Mutating Expert Compression:LorExperts and BTExperts
TL;DR
LorExperts and BTExperts are new methods for compressing Mixture-of-Experts (MoE) language models, achieving around 50% expert compression while maintaining accuracy. These techniques cluster experts and utilize low-rank corrections, outperforming previous methods as the number of experts increases.
✦ Why It Matters
Consider implementing LorExperts to reduce model size without sacrificing performance in your applications.
Key Takeaways
- Explore LorExperts for efficient expert compression in language models.
- Utilize clustering to maintain model accuracy while reducing size.
- Implement reconstruction fine-tuning to enhance performance post-compression.
- Consider BTExperts for optimized inference-time computation.
How It Works
LorExperts clusters experts into functional communities, keeping one full-precision expert per cluster. The remaining experts are represented as low-rank corrections to this dominant expert, allowing for effective compression without losing the original routing mechanism.