Model Deployment

NeMo inference container contains modules and scripts to help export nemo LLM models to TensorRT-LLM and deploy NeMo LLM models to Triton inference server.

Use NeMo deploy module to serve TrensorRT-LLM model in Triton:


from nemo.export import TensorRTLLM from nemo.deploy import DeployPyTriton trt_llm_exporter = TensorRTLLM(model_dir="/opt/checkpoints/tmp_trt_llm_folder/") trt_llm_exporter.export(nemo_checkpoint_path="/opt/checkpoints/megatron_falcon.nemo", model_type="falcon", n_gpus=1) nm = DeployPyTriton(model=trt_llm_exporter, triton_model_name="FALCON-7B", port=8000) nm.deploy() nm.serve()

Previous Model Export to TensorRT-LLM
Next Deploying the NeMo Models in the NeMo Framework Inference Container
© Copyright 2023-2024, NVIDIA. Last updated on Jan 19, 2024.