contrastive-learning

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

A python library for self-supervised learning on images.

[ECCV2024] Video Foundation Models & Data for Multimodal Understanding

This repository is the official implementation of Disentangling Writer and Character Styles for Handwriting Generation (CVPR 2023)

Pocket-Sized Multimodal AI for content understanding and generation across multilingual texts, images, and 🔜 video, up to 5x faster than OpenAI CLIP and LLaVA 🖼️ & 🖋️

Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch

Train Models Contrastively in Pytorch

This repo contains the code for "VLM2Vec / MMEB" [ICLR 2025], "VLM2Vec-V2 / MMEB-V2" [TMLR 2026], and "MMEB-V3" [COLM 2026]

Run Effective Large Batch Contrastive Learning Beyond GPU/TPU Memory Constraint

The corresponding code from our paper "DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations". Do not hesitate to open an issue if you run into any trouble!

Reliable, minimal and scalable library for pretraining foundation and world models

[NAACL 2021] This is the code for our paper `Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach'.

[TPAMI 2023] Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification

Code for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation"

[NeurIPS 2021] COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining

Implementation of MaMMUT, a simple vision-encoder text-decoder architecture for multimodal tasks from Google, in Pytorch

The most impactful papers related to contrastive pretraining for multimodal models!

[ICLR 2025] - Cross the Gap: Exposing the Intra-modal Misalignment in CLIP via Modality Inversion

Wav2vec 2.0 Self-Supervised Pretraining

CrossCLR: Cross-modal Contrastive Learning For Multi-modal Video Representations, ICCV 2021