中文实体关系抽取，pytorch，bilstm+attention

NLP 领域常见任务的实现，包括新词发现、以及基于pytorch的词向量、中文文本分类、实体识别、摘要文本生成、句子相似度判断、三元组抽取、预训练模型等。

1. Use BERT, ALBERT and GPT2 as tensorflow2.0's layer. 2. Implement GCN, GAN, GIN and GraphSAGE based on message passing.

PyTorch implementation of some text classification models (HAN, fastText, BiLSTM-Attention, TextCNN, Transformer) | 文本分类

Use BiLSTM_attention, BERT, ALBERT, RoBERTa, XLNet model to classify the SST-2 data set based on pytorch

Implementation of papers for text classification task on SST-1/SST-2

Joint text classification on multiple levels with multiple labels, using a multi-head attention mechanism to wire two prediction tasks together.

中文情感分类 | 基于三分类的文本情感分析

Deep Learning Library for Text Classification.

An NLP research project utilizing the "cardiffnlp/twitter-roberta-base-sentiment-latest" pre-trained transformer for tweet tokenization. The project includes an attention-based biLSTM model that predicts sentiment labels for tweets as negative (-1), neutral (0), or positive (1).

# 2022 COMAP Problem C chosen (Bitcoin and Gold Quant Trading

Explainable Sentence-Level Sentiment Analysis – Final project for "Deep Natural Language Processing" course @ PoliTO

This repo contains all files needed to train and select NLP models for fake news detection

This project features a Next Word Prediction Model deployed via a FLASK API, implemented using a Bi-LSTM model with an attention layer.

Course project of CS247.

Binary Classification

Deep Learning based end-to-end solution for detecting fraudulent and spam messages across all your devices

The task of post modifier generation requires to automatically generate a post modifier phrase describing the target entity (an entity essentially refers to a noun but here we only consider people) that contextually fits in the input sentence.