Eurus-Holmes

Awesome-Multimodal-Research

A curated list of Multimodal Related Research.

CHABCNet

[CHABCNet] ABCNet on the Chinese dataset, building on Detectron2 (Facebook AI Research)

SynthText_CH

[SynthText Chinese] Improved code for generating synthetic text images as described in "Synthetic Data for Text Localisation in Natural Images", Ankush Gupta, Andrea Vedaldi, Andrew Zisserman, CVPR 2016.

Heterogeneous_Sampling

Eurus-Holmes

GNNPapers

MT-Reading-List

A machine translation reading list maintained by Tsinghua Natural Language Processing Group

ai-deadlines

:alarm_clock: AI conference deadline countdowns

bert

TensorFlow code and pre-trained models for BERT

CMU-MultimodalSDK

CMU MultimodalSDK is a machine learning platform for development of advanced multimodal models as well as easily accessing advanced multimodal datasets.

deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

leetcode-program

LeetCode practice task generator.

nematus

Open-Source Neural Machine Translation in Tensorflow

nni

An open source AutoML toolkit for neural architecture search and hyper-parameter tuning. https://microsoft.github.io/nni/

OpenNMT-py

Open Source Neural Machine Translation in PyTorch

reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

github-readme-stats

:zap: Dynamically generated stats for your github readmes

julia

The Julia Language: A fresh approach to technical computing.

Multimodal-Attack

AdelaiDet

AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.

awesome-sentiment-analysis

Reading list for Awesome Sentiment Analysis papers

CS269-projects-2022spring

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

diffq

DiffQ performs differentiable quantization using pseudo quantization noise. It can automatically tune the number of bits used per weight or group of weights, in order to achieve a given trade-off between model size and accuracy.

gemma

Open weights LLM from Google DeepMind.

gemma_pytorch

The official PyTorch implementation of Google's Gemma models

latent-diffusion

High-Resolution Image Synthesis with Latent Diffusion Models

llama

Inference code for LLaMA models

Summer2022-Internships-1

Collection of Summer 2022 tech internships!

unilm

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities