I do have a notebook that does a PCA reduction to plot a similarity space: https://github.com/pamelafox/vector-embeddings-demos/blob/ma...

But as I noted in another comment, I think it loses so much information as to be deceiving.

I also find this 3d visualization to be fun: https://projector.tensorflow.org/

But once again, huge loss in information.

I personally learn more by actually seeing the relative similarity ranking and scores within a dataset, versus trying to visualize all of the nodes on the same graph with a massive dimension simplification.

That 3d visualization is what originally intrigued me though, to see how else I could visualize. :)