Visualizing embeddings in 3D

# Visualizing embeddings in 3D The example uses [PCA](https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html) to reduce the dimensionality of the embeddings from 1536 to 3. Then we can visualize the data points in a 3D plot. The small dataset `dbpedia_samples.jsonl` is curated by randomly sampling 200 samples from [DBpedia validation dataset](https://www.kaggle.com/danofer/dbpedia-classes?select=DBPEDIA_val.csv). ### 1. Load the dataset and query embeddings ### 2. Reduce the embedding dimensionality