Popular GitHub Repositories for Deberta

Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"

The implementation of DeBERTa

Unattended Lightweight Text Classifiers with LLM Embeddings

Calculate perplexity on a text with pre-trained language models. Support MLM (eg. DeBERTa), recurrent LM (eg. GPT3), and encoder-decoder LM (eg. Flan-T5).

PII Masker is an open-source tool for protecting sensitive data by automatically detecting and masking PII using advanced AI, powered by DeBERTa-v3. It provides high-precision detection, scalable performance, and a simple Python API for seamless integration into workflows, ensuring privacy compliance in various industries.

?Samsung AI Challenge 2021 1? ???????

Tokenizer POS-Tagger and Dependency-parser with BERT/RoBERTa/DeBERTa/GPT models for Japanese and other languages

Efficient and Scalable Estimation of Tool Representations in Vector Space

A multilingual DeBERTa model fine-tuned on political communication to classify discrete emotions

对DeBERTa v3模型进行微调，用于情感识别任务

Detect or classify input sentences as grammatically correct or incorrect by fine-tuning pre-trained DeBERTa-v3 model

Implement named entity recognition (NER) using regex and fine-tuned LLM, with a total of 15 categories. The ultimate goal is to apply the model to detect personally identifiable information (PII) in student writing.

COREG with Transformers Exploration: This research project delves into enhancing the COREG algorithm by incorporating transformer models, particularly DistilBERT and DeBERTa. Through rigorous experimentation on various GPU-equipped platforms, the modified COREG seeks to identify confident labels based on the predictions' similarity between models.

Application for training the pretrained transformer model DeBERTaV3 on an Aspect Based Sentiment Analysis task

Scraping paper data, preprocessed and trained using BERT variants, deployment and an integration to website

Finetuning Large Language Models

Code for the paper "ELLEN: Extremely Lightly Supervised Learning For Efficient Named Entity Recognition" (LREC-COLING 2024)

GPT 3.5 FineTuning

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).

Reproduce a prompt-learning method: P-Tuning V2, from the paper 《P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks》, model usage: Deberta + ChatGLM2, additional_task: RACE