Transformer models from BERT to GPT-4, environments from Hugging Face to OpenAI. Fine-tuning, training, and prompt engineering examples. A bonus section with ChatGPT, GPT-3.5-turbo, GPT-4, and DALL-E including jump starting GPT-4, speech-to-text, text-to-speech, text to image generation with DALL-E, Google Cloud AI,HuggingGPT, and more

Transformers 3rd Edition

[NAACL 2021] This is the code for our paper `Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach'.

The purpose of this repository is to introduce new dialogue-level commonsense inference datasets and tasks. We chose dialogues as the data source because dialogues are known to be complex and rich in commonsense.

A quantitative study on over 1.25 million tweets about ChatGPT, employed data scrapping, data cleaning, EDA, topic modeling, and sentiment analysis.

NLP model zoo for Russian

Topic clustering library built on Transformer embeddings and cosine similarity metrics.Compatible with all BERT base transformers from huggingface.

This app Classifies the text generated by AI tools like chatGPT. Roberta-base-openai-detector Model has been used from hugging face to detect ai generated texts.

PyTorch implementation of Sentiment Analysis of the long texts written in Serbian language (which is underused language) using pretrained Multilingual RoBERTa based model (XLM-R) on the small dataset.

This repository contains the code of our winning solution for the Shared Task on Detecting Signs of Depression from Social Media Text at LT-EDI-ACL2022.

Sentiment Analysis of tweets written in underused Slavic languages (Serbian, Bosnian and Croatian) using pretrained multilingual RoBERTa based model XLM-R on 2 different datasets.

This is a project of twitter sentiment analysis using machine learning(Support Vector Machines,Naive Bayes), deep learning(LSTM), Transformer(BERT,ROBERTA).

Source code for CoNLL 2021 paper by Huebner et al. 2021

text security audit 安全审核-语义模型过滤 敏感内容检测系统

Convert pretrained RoBerta models to various long-document transformer models

CatIss is an intelligent tool for automatic categorization of issue reports based on the RoBERTa model.

This repository contains the solutions to three problem statements completed during the hackathon. Each problem statement is categorized based on its difficulty level: Easy, Moderate, and Hard.

A project demonstrating the use of Large Language Models (LLMs) for text classification using the RoBERTa model.

A Java NLP application that identifies names, organizations, and locations in text by utilizing Hugging Face's RoBERTa NER model through the ONNX runtime and the Deep Java Library.

It is the nlp task to classify empathetic dialogues datasets using RoBERTa, ERNIE-2.0 and XLNet with different preprocessing method. You can get some detailed introduction and experimental results in the link below.