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jeff654's Projects

adversarial_text icon adversarial_text

Code for Adversarial Training Methods for Semi-Supervised Text Classification

awesome-python icon awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

bert icon bert

TensorFlow code and pre-trained models for BERT

chinese-bert-wwm icon chinese-bert-wwm

Pre-Training with Whole Word Masking for Chinese BERT(中文BERT-wwm预训练模型)

dive-into-dl-pytorch icon dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

dl4s icon dl4s

source code accompanying "Deep Learning for Search" book

dowhy icon dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

easytransfer icon easytransfer

EasyTransfer is designed to make the development of transfer learning in NLP applications easier.

few_shot_learning icon few_shot_learning

classical model code implementation of few-shot/one-shot lenaring, including siamese network, prototypical network, relation network, induction network

gt-nlp-class icon gt-nlp-class

Course materials for Georgia Tech CS 4650 and 7650, "Natural Language"

keras-textclassification icon keras-textclassification

中文长文本分类、短句子分类(Chinese Text Classification of Keras NLP, or sentence classify, long or short),字词句向量嵌入层(embeddings)和网络层(graph)构建基类,FastText,TextCNN,CharCNN,TextRNN, RCNN, DCNN, DPCNN, VDCNN, CRNN, Bert, Attention, DeepMoji, HAN, 胶囊网络-CapsuleNet, Transformer-encode, Seq2seq, ENT, DMN,

linformer-pytorch icon linformer-pytorch

My take on a practical implementation of Linformer for Pytorch. https://arxiv.org/pdf/2006.04768.pdf

llm-cookbook icon llm-cookbook

面向开发者的 LLM 入门教程,吴恩达大模型系列课程中文版

llmspracticalguide icon llmspracticalguide

A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers)

llmsurvey icon llmsurvey

The official GitHub page for the survey paper "A Survey of Large Language Models".

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