Do you have experience with model serving frameworks for deployment of ML models on GPU at scale such as Torchserve/TFServing/Triton/KFServing? If yes, please mention the project in brief.
Question
Do you have experience with model serving frameworks for deployment of ML models on GPU at scale such as Torchserve/TFServing/Triton/KFServing? If yes, please mention the project in brief.
Solution
Yes, I have experience with model serving frameworks for deployment of ML models on GPU at scale. One project I worked on involved using Torchserve for serving deep learning models. Torchserve is a powerful framework that allows for efficient deployment and scaling of PyTorch models. It provides features like multi-model serving, dynamic batching, and GPU acceleration, which are crucial for serving ML models at scale. With Torchserve, we were able to deploy our models on GPU instances and handle high request loads effectively.
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