Working with the embeddings

The embeddings are available as numpy files, where each row is a 768-dimension floating point embedding. Each row is associated with it's matching index in the metadata files.

Open an embedding file

The files are in numpy format, and can be opened with numpy in Python.

import numpy as np
embeddings = np.load('pd12m.01.npy')

Join Embeddings to Metadata

If you already have the metadata files loaded with pandas, you can join the embeddings to the dataframe simply.

df["embeddings"] = embeddings.tolist()

Alternatively, you could use a 0-based index to access both the metadata and associated embedding.

i = 300
metadata = df.iloc[i]
embedding = embeddings[i]