LLMKube Now Deploys Any Inference Engine, Not Just llama.cpp

1. 1Define a Model and InferenceService using LLMKube
2. 2Choose the desired inference engine, such as vLLM or Triton
3. 3Configure the controller to handle GPU scheduling, health probes, and metrics
4. 4Deploy the model using LLMKube's Kubernetes operator

DevOps and AI engineers on a team can benefit from this update as it allows for more flexibility in deploying different inference engines, making it easier to manage and optimize AI models

💡 LLMKube's update allows for more flexibility in deploying different inference engines, making it easier to manage and optimize AI models

🚀 LLMKube now deploys any inference engine! 🤖