From the course: MLOps Tools: MLflow and Hugging Face
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Connecting MLflow to Databricks - Hugging Face Tutorial
From the course: MLOps Tools: MLflow and Hugging Face
Connecting MLflow to Databricks
- [Instructor] There are a couple of things I want to show you here on how to connect MLflow to Databricks. There you have several options, and MLflow is pretty flexible. Let's start here with the documentation from Databricks itself. It doesn't matter here that it's referencing Amazon Web Services, because any of these will work. As you know, you can install MLflow locally, and what you want is to make sure that everything is connected. So here, it goes about the talking about the community edition, but don't worry about that. It really doesn't matter. What you need to, whenever you're configuring MLflow to communicates with a Databricks hosted tracking server, is to ensure that you are exporting the MLflow tracking URI, and here, this might not look correct, it might look like this is an example, but it isn't. What it needs here is Databricks. And optionally, you can use Databricks username and password if you want to authenticate straight away, or you can generate a rest API token.…
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