Link-Context-Learning

ML image recognition model

An implementation of a multimodal learning approach to improve language models' ability to recognize unseen images and understand novel concepts.

GitHub

91 stars
5 watching
8 forks
Language: Python
last commit: over 2 years ago
cvpr2024

Related projects:

RepositoryDescriptionStars
titsuki/raku-algorithm-libsvmA Raku binding for the popular machine learning library libsvm, providing an interface to support training and evaluating Support Vector Machines.8
gink03/alt-i2vAn implementation of a deep learning-based image representation learning approach using a modified fully connected layer and transfer learning from VGG1634
fukuball/fuku-mlAn easy-to-use machine learning library with various algorithms for classification and regression tasks.281
ryuk17/machinelearningThis is a collection of machine learning algorithms implemented in Python 3.6.103
kei500/liblinear-rubyProvides an interface to train and predict with machine learning models using LIBLINEAR83
360cvgroup/360vlA large multi-modal model developed using the Llama3 language model, designed to improve image understanding capabilities.32
ankane/epsA machine learning library for Ruby that allows users to build predictive models quickly and easily.659
uw-madison-lee-lab/cobsatProvides a benchmarking framework and dataset for evaluating the performance of large language models in text-to-image tasks30
masatoi/cl-online-learningA collection of machine learning algorithms for online linear classification50
lancopku/iaisThis project proposes a novel method for calibrating attention distributions in multimodal models to improve contextualized representations of image-text pairs.30
zhengpeng7/birefnetAn open-source implementation of an image segmentation model that combines background removal and object detection capabilities.1,484
eightbec/fastapi-ml-skeletonA FastAPI-based framework for serving machine learning models in production-ready applications412
aria42/inferA Clojure-based library for building machine learning and statistical models in a flexible and composable way.176
zk-ml/researchResearch on integrating machine learning with emergent runtimes to improve performance and security.22
arthurpaulino/miraimlAn asynchronous engine for continuous and autonomous machine learning26