A Linguistic Evaluation of Machine-Generated “Real” and “Fake” News
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Updated
Aug 14, 2022 - TeX
A Linguistic Evaluation of Machine-Generated “Real” and “Fake” News
An Empirical Study of Multitask Learning to Improve Open Domain Dialogue Systems, NoDaLiDa 2023
I performed sentiment analysis aimed at determining the sentiment of 50000 imDB movie reviews, whether they are positive, negative, or neutral. I employed various NLP approaches including lexicon based approaches, machine learning models, PLM models, and hybrid models, and assessed the performance on each type of model.
Auto generate tweets powered by pre-trained GPT2 based large language model (LLM) available offline.
Machine Learning Project. Please refer to my presentation-https://github.com/gongl1/projectdemo3/blob/main/Pattern%20Patent_ML.pptx - python, transformers, gpt2, nlp, sk-learn
Team project - generate recipe based on ingredients available in the fridge
Testing of the possible use of transformers model for various NLP tasks leveraging BERT pretrained model from Hugginface
A Series on Optimizing Transformer-Based Models
The script continuously listens for voice commands, processes them, and executes the corresponding actions based on predefined commands or generates responses using the GPT-2 model if the command is not recognized.
KoGPT2 이용하여 플레이리스트 이름 생성하기. KoGPT2 FineTuning cased
Use GPT2 to generate funny semi-realistic Discord dialogues
Pre-ALPHA, une simple chatbox pour hergement local de chat GPT-3 -2 ,...
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