forked from facebookresearch/LASER
-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Loading status checks…
Add laser clustering example notebook
1 parent
995c2f7
commit a934ac7
Showing
2 changed files
with
6,120 additions
and
0 deletions.
There are no files selected for viewing
Large diffs are not rendered by default.
Oops, something went wrong.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,13 @@ | ||
# Laser Encoder: Sentiment Analysis | ||
|
||
## Overview | ||
|
||
In this tutorial, we'll explore the power of Language-Agnostic SEntence Representations ([LASER](https://github.com/facebookresearch/LASER)) for generating multilingual embeddings. We'll then use these embeddings to perform clustering on the [MASSIVE](https://github.com/alexa/massive) dataset. Our goal was to show that LASER embeddings can effectively group texts not only by their thematic content but also across different languages. LASER can encode sentences from multiple languages into a shared embedding space, allowing for cross-lingual understanding and comparison. We'll see how this capability is useful for tasks like multilingual embeddings clustering. | ||
|
||
## Getting Started | ||
|
||
To run the notebook in Google Colab, simply click the "Open in Colab" button below: | ||
|
||
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Paulooh007/LASER-fork/blob/laser-clustering/tasks/clustering/LaserClusteringExample.ipynb) | ||
|
||
|