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adapt-fp

anm-frets-pyraformer

Reproduction of FreTS and Pyraformer with opensource codes

astra-network-analytical-all

This repository serves the role of an analytical network backend for ASTRA-sim. It models the latency and bandwidth for various network topologies.

astra-sim-all

ASTRA-sim2.0: Modeling Hierarchical Networks and Disaggregated Systems for Large-model Training at Scale

baidu-allreduce-starlab

config

C++ 的一个 Config 类的实现

cssummercamp2022

关于2022年CS保研夏令营通知公告的汇总。欢迎大家积极分享夏令营信息，资瓷一下互联网精神吼不吼啊？

cuemaker

手动CUE分轨文件生成辅助小程序

damai_tickets_modified

大麦个人备份

demo-routenet

Demo of RouteNet in ACM SIGCOMM'19

devign_lab_myversion

fixedpoint

Fixed Point C++ support for approximate computing

flex

The Fast Lexical Analyzer - scanner generator for lexing in C and C++

gans-collections-tf2.0_keras-eager_mode

This repository implements all kinds of GAN-models based on tensorflow2.0 keras API including GAN, CGAN, WGAN, WGAN_GP, VAE, CVAE, LSGAN, infoGAN, EBGAN, BEGAN, ACGAN

gitspace

centostest

gnnetworkingchallenge

RouteNet baseline for the Graph Neural Networking Challenge (https://bnn.upc.edu/challenge/)

gogogo

一个基于 Android 调试 API + 百度地图实现的虚拟定位工具，并且同时实现了一个可以自由移动的摇杆

hgs-cvrp

Modern implementation of the hybrid genetic search (HGS) algorithm specialized to the capacitated vehicle routing problem (CVRP). This code also includes an additional neighborhood called SWAP*.

hpac

hust-databaselab

HUST-DatabaseLab 2022

iact

iryo-demo

Iryo-test

lab-of-analysis-of-big-data

Lab of Analysis of Big-Data HUST

lab-of-computer-network

Lab of Computer Network

lab-of-machine-learning

Lab of Machine Learning HUST

lab-of-os

Lab of OS HUST

lab-of-principles-of-computer-composition

Lab of Principles of Computer Composition HUST

langchain-chatglm

langchain-ChatGLM, local knowledge based ChatGLM with langchain ｜ 基于本地知识库的 ChatGLM 问答

lert

LERT: A Linguistically-motivated Pre-trained Language Model（语言学信息增强的预训练模型LERT）

llm-blender

[ACL2023] We introduce LLM-Blender, an innovative ensembling framework to attain consistently superior performance by leveraging the diverse strengths of multiple open-source LLMs. LLM-Blender cut the weaknesses through ranking and integrate the strengths through fusing generation to enhance the capability of LLMs.