GPT is a Transformer-based architecture and training procedure for natural language processing tasks. Training follows a two-stage procedure. First, a language modeling objective is used on the unlabeled data to learn the initial parameters of a neural network model. Subsequently, these parameters are adapted to a target task using the corresponding supervised objective.
Source: Improving Language Understanding by Generative Pre-TrainingPaper | Code | Results | Date | Stars |
---|
Task | Papers | Share |
---|---|---|
Language Modelling | 56 | 6.94% |
Language Modeling | 46 | 5.70% |
Large Language Model | 41 | 5.08% |
Retrieval | 27 | 3.35% |
Question Answering | 24 | 2.97% |
Text Generation | 24 | 2.97% |
Prompt Engineering | 23 | 2.85% |
RAG | 22 | 2.73% |
Fairness | 16 | 1.98% |