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omg_bread t1_iurkaa1 wrote

Is there a link to the project page?

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SameerMohair t1_iut070w wrote

How does this work when you have embeddings on a vector space of many many dimensions, like google’s name2vec.

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Leopiney OP t1_iuup3jm wrote

Replying to SameerMohair (#429,970)

Hi there! Great question.

In these examples it happens exactly the same, the embeddings have large dimensionalities. What we show is a 2D projection of the embeddings so that we can plot them, regardless of the dimension of the embeddings.

You can choose between UMAP or PCA projections by default.

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jegerarthur t1_iuv8j5n wrote

What about the performances? Can it handle big dataset, like imagenet 21k ?

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Leopiney OP t1_iuxyxm4 wrote

Hey everyone! We released this open-source tool for tracking and comparing embedding experiments, which we regularly do.

Feel free to give it a try! Getting started is easy: https://github.com/pentoai/vectory

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