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muximuxi's Projects

gnnpapers icon gnnpapers

Must-read papers on graph neural network (GNN)

gpt-2 icon gpt-2

Code for the paper "Language Models are Unsupervised Multitask Learners"

gymnasium icon gymnasium

A standard API for reinforcement learning and a diverse set of reference environments (formerly Gym)

hyperlearn icon hyperlearn

50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster

hyperopt icon hyperopt

Distributed Asynchronous Hyperparameter Optimization in Python

imbalanced-semi-self icon imbalanced-semi-self

[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning

kg-demo-for-movie icon kg-demo-for-movie

从无到有构建一个电影知识图谱,并基于该KG,开发一个简易的KBQA程序。

knover icon knover

Large-scale open domain KNOwledge grounded conVERsation system based on PaddlePaddle

label-studio icon label-studio

Label Studio is a multi-type data labeling and annotation tool with standardized output format

lamcts icon lamcts

The release codes of LA-MCTS with its application to Neural Architecture Search.

lightseq icon lightseq

LightSeq: A High Performance Library for Sequence Processing and Generation

megatron-lm icon megatron-lm

Ongoing research training transformer language models at scale, including: BERT

mesh icon mesh

Mesh TensorFlow: Model Parallelism Made Easier

minlp icon minlp

XiaoMi Natural Language Processing Toolkits

mitie icon mitie

MITIE: library and tools for information extraction

models icon models

Models and examples built with TensorFlow

models-1 icon models-1

Pre-trained and Reproduced Deep Learning Models (『飞桨』官方模型库,包含多种学术前沿和工业场景验证的深度学习模型)

moss icon moss

An open-source tool-augmented conversational language model from Fudan University

mt-dnn icon mt-dnn

Multi-Task Deep Neural Networks for Natural Language Understanding

muse-maskgit-pytorch icon muse-maskgit-pytorch

Implementation of Muse: Text-to-Image Generation via Masked Generative Transformers, in Pytorch

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