Module 11: LLM Deployment
๐ฏ Learning Objectivesโ
- Deploy and serve LLMs at scale with vLLM and TGI
- Optimize inference with quantization and batching
- Implement effective cost management strategies
๐ Module Contentโ
Chapter 1: Serving LLMs at Scaleโ
vLLM, TGI, inference optimization, batching strategies, streaming.
Chapter 2: Inference Optimizationโ
Quantization in production, speculative decoding, KV cache optimization.
Chapter 3: Cost Managementโ
Token tracking, caching strategies, model selection, rate limiting.
๐ Let's Begin!โ
Start with Chapter 1: Serving LLMs at Scale.