JEONGSEJIN

AI_Courses

Algorithm

Computer Algorithm

CloudLibrary

Code-Test-Study

코딩 테스트 관련 기출문항을 풀어보고 소스코드 및 설명을 업로드합니다. (문제 추천은 Discussions에 들어가셔서 자유롭게 가능합니다.)

Coding-Practice

Space to improve my coding skills

DataStructure

Data Structure Code By Python

DPR

Dense Passage Retriever - is a set of tools and models for open domain Q&A task.

JEONGSEJIN.github.io

OneDayOneCoding

1일 1코딩

PyTorch-DeepLearning

JEONGSEJIN/DataStructure

Data Structure Code By Python

JEONGSEJIN/Coding-Practice

Space to improve my coding skills

JEONGSEJIN/JEONGSEJIN.github.io

JEONGSEJIN/OneDayOneCoding

1일 1코딩

JEONGSEJIN/AI_Courses

JEONGSEJIN/CloudLibrary

JEONGSEJIN/Code-Test-Study

코딩 테스트 관련 기출문항을 풀어보고 소스코드 및 설명을 업로드합니다. (문제 추천은 Discussions에 들어가셔서 자유롭게 가능합니다.)

JEONGSEJIN/DPR

Dense Passage Retriever - is a set of tools and models for open domain Q&A task.

JEONGSEJIN/Fouier-Series

선형대수학

JEONGSEJIN/JEONGSEJIN

Main screen

JEONGSEJIN/HaluEval

This is the repository of HaluEval, a large-scale hallucination evaluation benchmark for Large Language Models.

JEONGSEJIN/KnowHalu

JEONGSEJIN/korquad.github.io

Korean wiki QA dataset for MRC

JEONGSEJIN/kss

Kss: A Toolkit for Korean sentence segmentation

JEONGSEJIN/language

Shared repository for open-sourced projects from the Google AI Language team.

JEONGSEJIN/llama

Inference code for Llama models

JEONGSEJIN/Machine-Learning

최적화론, 머신러닝 공부한 저장소

JEONGSEJIN/neural-networks-from-numpy

The NumPy adaptation of “neural-networks-from-scratch” repository by Minh-Chien Trinh, crafted for Deep Learning Study by Sejin Jeong.

JEONGSEJIN/neural-networks-from-scratch

The Jupyter Notebook adaption of “Neural Networks from Scratch in Python” by Harrison and Daniel, crafted for utilization as teaching resources in the graduate course titled “Deep Learning”, offered during the Spring 2024 semester at Jeonbuk National University, by Minh-Chien Trinh.

JEONGSEJIN/ProphetNet

A research project for natural language generation, containing the official implementations by MSRA NLC team.

JEONGSEJIN/rag-from-scratch

JEONGSEJIN/self-rag

This includes the original implementation of SELF-RAG: Learning to Retrieve, Generate and Critique through self-reflection by Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi.

JEONGSEJIN/selfcheckgpt

SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models

JEONGSEJIN/speech_recognition

Speech recognition module for Python, supporting several engines and APIs, online and offline.

JEONGSEJIN/summarization

summarization

JEONGSEJIN/Swift

env is VSCode

JEONGSEJIN/tensorflow-nlp-tutorial

tensorflow를 사용하여 텍스트 전처리부터, Topic Models, BERT, GPT와 같은 최신 모델의 다운스트림 태스크들을 정리한 Deep Learning NLP 저장소입니다.

JEONGSEJIN/transformers

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

JEONGSEJIN/TruthfulQA

TruthfulQA: Measuring How Models Imitate Human Falsehoods

JEONGSEJIN/TruthX

TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space