ChristophAlt/pytorch-starspace
PyTorch implementation of StarSpace as described in "StarSpace: Embed All The Things!" by Ledell Wu, Adam Fisch, Sumit Chopra, Keith Adams, Antoine Bordes and Jason Weston
This helps machine learning engineers or researchers working with PyTorch to train models that understand relationships between different types of data, such as text documents. You provide a dataset of various items, and it generates numerical representations (embeddings) that capture their semantic similarities. This allows for tasks like classifying news articles or finding related content.
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Use this if you are a machine learning practitioner looking for a PyTorch-based tool to create embeddings that connect diverse data types, especially for text analysis or recommendation systems.
Not ideal if you need a fully featured, production-ready StarSpace implementation, as this version is still under development and does not yet match the original C++ functionality.
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Python
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Last pushed
Apr 24, 2018
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