A typical recipe for improving LLMs involves multiple stages: synthetic data generation (SDG), model training through supervised fine-tuning (SFT) or reinforcement learning (RL), and model evaluation. Each stage requires using different libraries, which are often challenging to set up and difficult to use together. For example, you might use NVIDIA TensorRT-LLM or vLLM for SDG and NVIDIA��
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