Language models are statistical and machine learning models that predict the probability of a sequence of words. They are a key component in natural language processing (NLP).
Applications of language models:
- Autocomplete: Predicting the next words while typing.
- Machine translation: Converting text from one language to another.
- Text generation: Creating coherent and meaningful text based on given input.
- Sentiment analysis: Evaluating the emotions expressed in text.
- Speech recognition: Converting speech into text.
- Chatbots and virtual assistants: Creating interactive conversational agents.
Popular language models:
- GPT-3: A text generation model developed by OpenAI, known for producing human-like text based on prompts.
- BERT: A model developed by Google, used for NLP tasks such as text classification and question answering.
- Transformer: A model architecture used in many modern language models, including GPT-3 and BERT.
Language models are a crucial tool in modern NLP applications, enabling computers to better understand and generate human language.