sauronlee Goto Github PK

algorithmsbypython

算法/数据结构/Python/剑指offer/机器学习/leetcode

bert-ner-pytorch

Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)

books

My book list

daily-routine

finding-nlp-papers

This repository provides the source codes of "Finding NLP Papers by Asking a Multi-hop Question" published in Special Interest Group on Spoken Language Understanding and Dialogue Processing (SIG-SLUD) 2022

fully-hyperbolic-nn

Code for paper Fully Hyperbolic Neural Networks

gat-cobo

gsr

ja_we_sim

just-the-docs

A modern, high customizable, responsive Jekyll theme for documention with built-in search.

memory-game

momory-game object-oriented progromming es6 css3

ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

ml-notes

nlpdataset

记录本人整理的一些数据集

node2vec-tool

paper-kg

Paper-KG For Conversational Paper Recommender Systems

pyannote-audio

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

pytorch_template

ququevaluation.github.io

An evaluation method for evaluating the quality of multi-hop questions or multi-entity sentences, etc.

sauronlee.github.io

semanticinterlanguagelinks

Allows to create and manage interlanguage links semantically.

semcal.app-for-sist

skb-da

This repository provides the source codes of "A Data Augmentation Method for Building Sememe Knowledge Base via Reconstructing Dictionary Definitions" published in The Association for Natural Language Processing 2022

skb-stc

This repository provides the source codes of "The Endeavour to Advance Short Text Classification: Using Heterogeneous Graph Neural Network via Building Sememe-relationships (JSAI) 2022

skip_gram_embadding

Skip_gram embadding for Pytorch

splitting-and-splicing-of-speech

This repository contains code and models for the poster: wav2vecモデルによる方言音声資料のテキスト化 (LRW2022).

swift4nlp

swiftnotes

todos

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.