EdoardoBotta/RQ-VAE-Recommender
[Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"
This project helps e-commerce businesses and content platforms generate better recommendations for users. By analyzing historical data of how users interact with items (like products or movies), it can predict and suggest the next item a user is likely to engage with. This is ideal for product managers or data scientists working on improving recommendation engines.
747 stars. No commits in the last 6 months.
Use this if you need to build or enhance a generative recommendation system that suggests sequences of items based on past user behavior.
Not ideal if you're looking for a simple, off-the-shelf recommendation solution without the need for deep learning model training and customization.
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747
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107
Language
Python
License
MIT
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Last pushed
Sep 22, 2025
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