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BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [3]
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation.LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.
Template documentation This template's initial visibility currently defaults to autocollapse , meaning that if there is another collapsible item on the page (a navbox, sidebar , or table with the collapsible attribute ), it is hidden apart from its title bar; if not, it is fully visible.
In the more general case of the clausal form of first-order logic, resolution is a single, axiom-free rule of inference, in which a problem is solved by proving a contradiction from premises that include the negation of the problem to be solved. [83] Inference in both Horn clause logic and first-order logic is undecidable, and therefore ...
Apart from the a possibility that saving an LLM output may cause verbatim non-free content to be carried over to the article, these models can produce derivative works. For example, an LLM can rephrase a copyrighted text using fewer, the same, or more words than the original – editors should mind the distinction between a summary and an ...
The bag-of-words model (BoW) is a model of text which uses an unordered collection (a "bag") of words.It is used in natural language processing and information retrieval (IR).
Templates are normally placed in the template namespace, though you can place a template intended for your own personal use or for experimentation in your own user space. Before creating a template, do a quick search for existing templates (such as by exploring Category:Wikipedia templates) to see if there is already a template that does what ...
This page in a nutshell: Avoid using large language models (LLMs) to write original content or generate references. LLMs can be used for certain tasks (like copyediting, summarization, and paraphrasing) if the editor has substantial prior experience in the intended task and rigorously scrutinizes the results before publishing them.