triton-inference-server/model_navigator

Triton Model Navigator is an inference toolkit designed for optimizing and deploying Deep Learning models with a focus on NVIDIA GPUs.

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Established

This tool helps machine learning engineers and MLOps specialists streamline the deployment of deep learning models and pipelines, especially for inference on NVIDIA GPUs. It takes models built in PyTorch, TensorFlow, or ONNX, optimizes them, and outputs highly performant models ready for serving on Triton Inference Server or PyTriton.

218 stars.

Use this if you need to optimize and deploy your deep learning models or entire inference pipelines for maximum performance on NVIDIA GPUs, ensuring correctness and efficiency.

Not ideal if you are not working with deep learning models, do not use NVIDIA GPUs for inference, or are not concerned with optimizing model performance for production deployment.

deep-learning-deployment MLOps model-optimization GPU-acceleration inference-serving

No Package No Dependents

Maintenance 10 / 25

Adoption 10 / 25

Maturity 16 / 25

Community 16 / 25

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Stars

218

Forks

Language

Python

License

Apache-2.0

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model_navigator and model_analyzer

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