Shypd.aiThe largest open index of AI toolsRQ-VAE-Recommender is an Open Source & Models tool that provides a PyTorch implementation of a generative retrieval model. It uses semantic IDs from RQ-VAE for building recommender systems.
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RQ-VAE-Recommender offers a PyTorch implementation of a generative retrieval model, specifically designed for recommender systems. The model operates in two stages: first, it maps items in a corpus to a tuple of semantic IDs by training an RQ-VAE. Second, it tokenizes sequences of these semantic IDs using a frozen RQ-VAE and then trains a transformer-based model to predict the next IDs in the sequence. This approach is based on the research presented in "Recommender Systems with Generative Retrieval." It supports various datasets, including Amazon Reviews (Beauty, Sports, Toys), MovieLens 1M, and MovieLens 32M, and provides both RQ-VAE and decoder-only retrieval model training scripts. Pre-trained checkpoints are available on Hugging Face for Amazon Beauty.
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