embedding-atlas 0.7.1

A tool for visualizing embeddings

Embedding Atlas

A Python package that provides a command line tool to visualize a dataset with embeddings. It also includes a Jupyter widget and a Streamlit widget.

• Documentation: https://apple.github.io/embedding-atlas
• GitHub: https://github.com/apple/embedding-atlas

Installation

pip install embedding-atlas

and then launch the command line tool:

embedding-atlas [OPTIONS] INPUTS...

Loading Data

You can load your data in two ways: locally or from Hugging Face.

Loading Local Data

To get started with your own data, run:

embedding-atlas path_to_dataset.parquet

Loading Hugging Face Data

You can instead load datasets from Hugging Face:

embedding-atlas huggingface_org/dataset_name

Visualizing Embedding Projections

To visual embedding projections, pre-compute the X and Y coordinates, and specify the column names with --x and --y, such as:

embedding-atlas path_to_dataset.parquet --x projection_x --y projection_y

You may use the SentenceTransformers package to compute high-dimensional embeddings from text data, and then use the UMAP package to compute 2D projections.

You may also specify a column for pre-computed nearest neighbors:

embedding-atlas path_to_dataset.parquet --x projection_x --y projection_y --neighbors neighbors

The neighbors column should have values in the following format: {"ids": [id1, id2, ...], "distances": [d1, d2, ...]}. If this column is specified, you'll be able to see nearest neighbors for a selected point in the tool.