📄️ What is Luminous?
Luminous Model Family
📄️ Prompting & Completion
Generally speaking, our models attempt to find the best continuation for a given input. This is referred to as a completion in the world of Natural Language Processing (NLP). To find the best completion, we have to write good prompts, which are your input to the model. Our models continue the given prompt by choosing the most likely continuation from a probability distribution. Practically, this means that the model first recognizes the style of the prompt and then attempts to continue it accordingly. Depending on the task at hand, the structure and content of the prompt are essential to generating completions that match the input task.
📄️ Tokens
Language models can only work with data that is in a digestible format. In essence, such models comprise many large matrices containing floating point numbers. Matrices do not run on characters but on numbers. Therefore, sets of characters are “translated” into sets of integers, so-called tokens.