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How to implement RAG with TensorRT-LLM
Step-by-step guide: how to implement RAG using TensorRT-LLM.
This guide shows you how to implement RAG using TensorRT-LLM. Harch Corp provides GPU cloud infrastructure optimized for TensorRT-LLM with H100/H200 GPUs, 400G InfiniBand, and 47 gCO2/kWh carbon intensity.
1
Prerequisites: Set up your TensorRT-LLM environment on Harch Corp GPU cloud.
2
Configuration: Configure TensorRT-LLM for implement RAG.
3
Execution: Run your implement RAG workload. Monitor GPU utilization.
4
Optimization: Optimize for performance and cost.
5
Monitoring: Set up monitoring with Prometheus and Grafana.
6
Scaling: Scale to multiple GPUs with distributed training.
7
Deployment: Deploy your model to production.
8
Cost optimization: Use spot instances and auto-scaling.