Sign Up
Efficient LLM Inference (2023)
2024-01-04
•
Hacker News
•
Share on Twitter
•
Share on Linkedin
•
Copy link
Generate a sharable post
Summary:
The article discusses three main approaches to serving a given LLM more efficiently: quantization, distillation, and optimization.
Optimization is the first step to reduce overhead in code and improve performance.
Distillation is generally more effective than quantization in reducing model size while maintaining performance, but it can be costly.
Quantization is a cheaper option that reduces precision but sacrifices some accuracy for improved performance.
The tradeoff between distillation and quantization depends on the available resources and cost considerations.
See on HackerNews
See Full Article
made with 💙 by the team at
Newsprint