NiuTrans Open Source (@NiuTrans)
  • Stars
    star
    7,605
  • Global Org. Rank 3,094 (Top 1.0 %)
  • Registered over 6 years ago
  • Most used languages
    C++
    42.9 %
    Python
    28.6 %
    TeX
    14.3 %
    Cuda
    14.3 %
  • Location 🇨🇳 China
  • Country Total Rank 775
  • Country Ranking
    TeX
    14
    Cuda
    129
    C++
    329
    Python
    688

Top repositories

1

MTBook

《机器翻译:基础与模型》肖桐 朱靖波 著 - Machine Translation: Foundations and Models
TeX
2,712
star
2

ABigSurvey

A collection of 1000+ survey papers on Natural Language Processing (NLP) and Machine Learning (ML).
1,981
star
3

Classical-Modern

非常全的文言文(古文)-现代文平行语料
Python
1,077
star
4

CNSurvey

一份中文综述文章列表(自然语言处理&机器学习)
548
star
5

NiuTensor

NiuTensor is an open-source toolkit developed by a joint team from NLP Lab. at Northeastern University and the NiuTrans Team. It provides tensor utilities to create and train neural networks.
C++
379
star
6

ABigSurveyOfLLMs

A collection of 150+ surveys on LLMs
172
star
7

NiuTrans.SMT

NiuTrans.SMT is an open-source statistical machine translation system developed by a joint team from NLP Lab. at Northeastern University and the NiuTrans Team. The NiuTrans system is fully developed in C++ language. So it runs fast and uses less memory. Currently it supports phrase-based, hierarchical phrase-based and syntax-based (string-to-tree, tree-to-string and tree-to-tree) models for research-oriented studies.
C++
144
star
8

NiuTrans.NMT

A Fast Neural Machine Translation System developed in C++.
C++
136
star
9

MT-paper-lists

MT paper lists (by conference)
123
star
10

NASPapers

Paper lists of neural architecture search (NAS)
121
star
11

LanguageCodes

We present a list of languages with their codes, families, regions and etc. We also present a list of multi-lingual corpora (with urls).
79
star
12

compiler-notes

60
star
13

Introduction-to-Transformers

An introduction to basic concepts of Transformers and key techniques of their recent advances.
46
star
14

Vision-LLM-Alignment

This repository contains the code for SFT, RLHF, and DPO, designed for vision-based LLMs, including the LLaVA models and the LLaMA-3.2-vision models.
Python
41
star
15

MTVenues

A list of conferences and journals relevant to machine translation
33
star
16

Hands-on-GEMM

A tutorial on GEMM
Cuda
7
star