From the course: Full-Stack Deep Learning with Python
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Workaround to get model artifacts on the local machine - Python Tutorial
From the course: Full-Stack Deep Learning with Python
Workaround to get model artifacts on the local machine
- [Instructor] Now early on in this course I had mentioned that because we needed to use a GPU, we couldn't train this convolutional neural network on our local machine and instead had to use Colab. We then set up ML flow on the Colab runtime and then used ML Flow to track our models, metrics, parameters, and artifacts. Now, here are our models, artifacts available on the Colab runtime, but they're not present on my local machine. I want to show you how we can deploy and serve this model using ML flow and we'll do that on our local machine. So what I need to do is download all of the artifacts that ML Flow has saved into this emnist letters classifier, CNN model, sub folder to the local machine. I've selected the model.path file under data, and I'm going to click on this download button, and this will download this into my downloads folder. And I'm going do this for every file under artifacts here. I'm going to download this…
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