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Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
Unattended Lightweight Text Classifiers with LLM Embeddings
Build a Large Language Model (From Scratch) book and Finetuned Models
🥇Samsung AI Challenge 2021 1등 솔루션입니다🥇
[ACL 2023] Solving Math Word Problems via Cooperative Reasoning induced Language Models (LLMs + MCTS + Self-Improvement)
DictABSA: A dictionary knowledge (entity description informations) enhanced aspect-based sentiment analysis (ABSA) code implementation
금융 도메인에 특화된 한국어 임베딩 모델
The implementation of DeBERTaV3-based commonsense question answering on CommonsenseQA.
Kaggle NLP competition - Top 2% solution (36/2060)
Application for training the pretrained transformer model DeBERTaV3 on an Aspect Based Sentiment Analysis task
Key Point Analysis: implementation of two-component system for performing Key Point Matching and Key Point Generation task with multiple PLMs.
Deberta implementation at Cross-Domain Sentiment Classification With Bidirectional Contextualized Transformer Language Models
The code of Hierarchical Multi-label Classification (HMC). It is a final course project of Natural Language Processing and Deep Learning, 2022 Fall.
Implementing science-related multiple-choice question answering based on LLMs and RAG.
Classification of medical texts to differentiate between human medical and veterinary subjects.
Scraping paper data, preprocessed and trained using BERT variants, deployment and an integration to website
Finetuning Large Language Models
This repository contains the code for submission made at SemEval 2022 Task 5: MAMI
Can you spot automatically generated scientific excerpts?
Backbone: 5 x DeBerta and Head: Rapids SVR
Data enrichment with experimental results of the paper 'Two is Better than Many? Binary Classification as an Effective Approach to Multi-Choice Question Answering'
Solutions to US patents phrase matching Kaggle competition https://www.kaggle.com/competitions/us-patent-phrase-to-phrase-matching
Some experiments to compare the performances of some pre-trained transformer models on a basic sentiment regression task
Automated-Essay-Scoring-Systems-with-NLP-Models
The study employed the Fast-LCF-ATEPC model for Alibaba (intl') reviews, achieving 91.06% APC accuracy and 83.09% ATE F1 score. It revealed mixed user experiences in areas like usability, pricing, and shipping, aiming to enhance Alibaba's e-commerce user satisfaction.
In this demo, we illustrate the the possibility of using Semantic Search + Recognising Textual Entailment with Gradio to build an automated fact checking tool
Document Clustering, Summarisation and Visualisation on 20NewsGroup
This project focuses on the Tachygraphy analysis i.e. Micro-Text analysis using Deep Learning techniques. The primary goal is to predict the simplified, expanded text from shorthand forms often found in casual digital communication. Additionally, the project aims to extract sentiments, emotions, personality traits, and other relevant information.
This repository contains the code, data, and models of the paper titled "Math Word Problem Solving by Generating Linguistic Variants of Problem Statements" published in the Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop).
A PyTorch Library for Sequence Labeling Tasks such as Named-entity Recognition or Part-of-speech Tagging