Add LLM token classification example

[roym899]

What

Adds an example that tokenizes a text, visualizes the embeddings for each token (as a 3D UMAP embedding), logs the text tokens linking to the corresponding embedding, and classifies each token. Classification is into named entities (person, location, organization, and misc). The found, unique named entities are also logged.

Also removed some newlines in manifest.yml to make it more consistent.

Checklist

• I have read and agree to Contributor Guide and the Code of Conduct
• I've included a screenshot or gif (if applicable)
• I have tested the web demo (if applicable):
  • Full build: app.rerun.io
  • Partial build: app.rerun.io - Useful for quick testing when changes do not affect examples in any way
• The PR title and labels are set such as to maximize their usefulness for the next release's CHANGELOG

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[teh-cmc]

Works great, looks great.

Please don't spawn debugging shells without my consent though 😛

[teh-cmc]

Also: at least on my machine, there's a bunch of wait time before the first logging calls arrive and again while computing the embeddings:

23-12-15_09.24.23.patched.mp4

It'd be nice if the script mentioned what it was doing in its standard output during those.

(Man i really wish we could log a spinner thing...)

[roym899]

Added a print.

Regarding runtime, the embeddings are currently computed twice. Once for logging and once as part of the whole pipeline. Not sure if it's worth to change this. In the pipeline there is a bit of extra stuff going on beyond just another function call passing the embeddings. So it'd add some complexity to the example. I added a note for now.

[teh-cmc]

Any reason we're not merging this @roym899 ?

[roym899]

Making some small adjustments after talking to @nikolausWest