There's nothing better than pre-trained, open-source models! You can use them to solve a variety of common problems, such as image classification, speech-to-text, or even text generation.

But the problem is - they come in different formats and shapes. From native PyTorch and Tensorflow, Hugging face, or Torch lightning, it can take quite some time to set those up for inference, finetuning, or evaluation.

In this episode, we hosted Patrick Barker from One Medical, who shared his unique solution to the problem, how they shaped it, and how this is all connected to Kubernetes.

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