sklearn-ranking

Learning to Rank in TensorFlow

Multi-Task Deep Neural Networks for Natural Language Understanding

A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine

An official implementation for "CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval"

allRank is a framework for training learning-to-rank neural models based on PyTorch.

Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & Collaborations.

Fast Differentiable Sorting and Ranking

“Chorus” of recommendation models: a light and flexible PyTorch framework for Top-K recommendation.

Case Recommender: A Flexible and Extensible Python Framework for Recommender Systems

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