Joel Jang 's repositories
music2video
Making an AI-generated music video from any song with Wav2CLIP and VQGAN-CLIP
continual-knowledge-learning
[ICLR 2022] Towards Continual Knowledge Learning of Language Models
knowledge-unlearning
[ACL 2023] Knowledge Unlearning for Mitigating Privacy Risks in Language Models
temporalwiki
[EMNLP 2022] TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Models
Pretraining_T5_custom_dataset
Continue Pretraining T5 on custom dataset based on available pretrained model checkpoints
Remaining-Useful-Life-Prediction
Remaining Useful Life prediction of machinery using a novel data wrangling method and CNN-LSTM network for prediction
negated-prompts-for-llms
[NeurIPS 2022 Workshop] A Case Study with Negated Prompts using T0 (3B, 11B), InstructGPT (350M-175B), GPT-3 (350M - 175B) & OPT (125M - 175B) LMs
salient-span-masking
Code used for salient span masking first proposed in "REALM: Retrieval-Augmented Language Model Pre-Training"
azcopy12-script
Simple scripts for downloading/uploading files & directories from azure blob storage using Azcopy v12
joeljang_outdated.github.io
A minimal Jekyll Theme to host your resume (CV)
Sequential-Targeting
Code for Sequential Targeting: A Continual Learning Approach for Data Imbalance in Text Classification
d2l-pytorch
This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.
DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
examples
This repository contains SavviHub examples
Folder-Structure-Conventions
Folder / directory structure options and naming conventions for software projects
guess
Using Solidity to create a block-chain based lottery application
KoBART-summarization
Summarization module based on KoBART
minimal-opt
Minimal inference of OPT models on different downstream tasks
multi-thread
Downloading images with multi-thread
TCC-Diving-Website
A simple website using HTML, CSS, and Javascript