Popular GitHub Repositories for Center Loss

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

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.

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

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

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

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

Code for the Lovász-Softmax loss (CVPR 2018)

Live training loss plot in Jupyter Notebook for Keras, PyTorch and others

Implementation of triplet loss in TensorFlow

Super Fast and Accurate 3D Object Detection based on 3D LiDAR Point Clouds (The PyTorch implementation)

A general representation model across vision, audio, language modalities. Paper: ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities

Convolutional Recurrent Neural Networks(CRNN) for Scene Text Recognition

Implementing Siamese networks with a contrastive loss for similarity learning

A library with extensible implementations of DPO, KTO, PPO, ORPO, and other human-aware loss functions (HALOs).