OmniNet

Multi-modal ML framework

An implementation of a unified architecture for multi-modal multi-task learning using PyTorch.

Official Pytorch implementation of "OmniNet: A unified architecture for multi-modal multi-task learning" | Authors: Subhojeet Pramanik, Priyanka Agrawal, Aman Hussain

GitHub

512 stars
19 watching
58 forks
Language: Python
last commit: about 4 years ago
artificial-intelligencedeep-learningimage-captioningmachine-learningmultimodal-learningmultitask-learningneural-networknlptransformervideo-recognition

Related projects:

Repository Description Stars
multimodal-art-projection/omnibench Evaluates and benchmarks multimodal language models' ability to process visual, acoustic, and textual inputs simultaneously. 14
open-mmlab/mmengine Provides a flexible and configurable framework for training deep learning models with PyTorch. 1,179
minqi/learning-to-communicate-pytorch This project implements a PyTorch-based framework for learning discrete communication protocols in multi-agent reinforcement learning environments. 346
oml-team/open-metric-learning A PyTorch-based framework for training and validating models that produce high-quality embeddings for computer vision and other tasks. 882
txwang/mogonet A framework for multi-omics data integration and classification using graph convolutional networks 143
open-mmlab/multimodal-gpt Trains a multimodal chatbot that combines visual and language instructions to generate responses 1,477
namisan/mt-dnn A PyTorch package implementing multi-task deep neural networks for natural language understanding 2,238
pmerienne/trident-ml A real-time online machine learning library built on top of Storm and Trident. 382
unslothai/hyperlearn An optimized machine learning framework using PyTorch that improves performance and efficiency on various hardware configurations 1,842
pku-yuangroup/moe-llava Develops a neural network architecture for multi-modal learning with large vision-language models 1,980
molcik/python-neuron A Python library for implementing and training various neural network architectures 40
okerew/okrolearn A Python machine learning library providing efficient array operations and neural network functionality 3
elbayadm/attn2d A PyTorch implementation of 2D convolutional neural networks for sequence-to-sequence prediction in machine translation 501
vlgiitr/dmn-plus A PyTorch implementation of an improved question answering architecture with dynamic memory networks and attention mechanisms 64
tristandeleu/pytorch-maml-rl Replication of Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks in PyTorch for reinforcement learning tasks 827