Popular GitHub Repositories for Hybrid Loss

A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.

Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database?.

An open source implementation of CLIP.

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

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

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

A Python implementation of LightFM, a hybrid recommendation algorithm.

The Cloud-Native API Gateway and AI Gateway

Siamese and triplet networks with online pair/triplet mining 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.

This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

??? 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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MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model.

Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)

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

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

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

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

Distributed vector search for AI-native applications