| 175 billion for GPT-3). | |
| M | |
| masked language modeling (MLM) | |
| A pretraining task where the model sees a corrupted version of the texts, usually done by | |
| masking some tokens randomly, and has to predict the original text. | |
| multimodal | |
| A task that combines texts with another kind of inputs (for instance images). | |
| N | |
| Natural language generation (NLG) | |
| All tasks related to generating text (for instance, Write With Transformers, translation). | |
| Natural language processing (NLP) | |
| A generic way to say "deal with texts". | |
| Natural language understanding (NLU) | |
| All tasks related to understanding what is in a text (for instance classifying the | |
| whole text, individual words). | |
| P | |
| pipeline | |
| A pipeline in 🤗 Transformers is an abstraction referring to a series of steps that are executed in a specific order to preprocess and transform data and return a prediction from a model. |