Popular GitHub Repositories for Ranking Loss

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

An open source implementation of CLIP.

? Scalable embedding, reasoning, ranking for images and sentences with CLIP

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

File Parser optimised for LLM Ingestion with no loss ? Parse PDFs, Docx, PPTx in a format that is ideal for LLMs.

Context aware, pluggable and customizable data protection and de-identification SDK for text and images

Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.

Torchreid: Deep learning person re-identification in PyTorch.

MiniMax-01 is a simple implementation of the MiniMax algorithm, a widely used strategy for decision-making in two-player turn-based games like Tic-Tac-Toe. The algorithm aims to minimize the maximum possible loss for the player, making it a popular choice for developing AI opponents in various game scenarios.

Siamese and triplet networks with online pair/triplet mining in PyTorch

??? 专注于YOLO11，YOLOv8、TYOLOv12、YOLOv10、RT-DETR、YOLOv7、YOLOv5改进模型，Support to improve backbone, neck, head, loss, IoU, NMS and other modules?

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Learning to Rank in TensorFlow

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

Multi-Task Deep Neural Networks for Natural Language Understanding

label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful

Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Ranking (CTR/CVR prediction), Post Ranking, Large Model (Generative Recommendation, LLM), Transfer learning, Reinforcement Learning and so on.

Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)

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

:dart: Task-oriented embedding tuning for BERT, CLIP, etc.