Главная
Study mode:
on
1
OpenAI output predictions, Cursor fast-apply, vLLM speculative decoding
2
Cursor Fast Apply - how it works
3
Video Overview
4
How does speculative decoding work?
5
Using OpenAI Output Predictions
6
Speculative Decoding with vLLM and Llama 8B
7
Speed-up and Costs of Output Predictions
8
Resources
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Learn advanced techniques for accelerating inference speeds in language models through this 24-minute technical video. Explore three key approaches to faster model outputs: OpenAI's output predictions, Cursor's fast-apply functionality, and vLLM's speculative decoding. Dive deep into the mechanics of speculative decoding, understand its implementation with vLLM and Llama 8B, and discover practical applications using OpenAI's prediction capabilities. Compare speed improvements and cost implications across different approaches while gaining hands-on experience with code examples and real-world applications. Access comprehensive resources including slides, documentation links, and implementation guides to enhance your understanding of these cutting-edge inference optimization techniques.

Faster Inference Using Output Predictions with OpenAI and vLLM

Trelis Research
Add to list
0:00 / 0:00