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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.
For example, a prompt may include a few examples for a model to learn from, such as asking the model to complete "maison → house, chat → cat, chien →" (the expected response being dog), [23] an approach called few-shot learning. [24] In-context learning is an emergent ability [25] of large language models.
A language model is a model of natural language. [1] Language models are useful for a variety of tasks, including speech recognition [2], machine translation, [3] natural language generation (generating more human-like text), optical character recognition, route optimization, [4] handwriting recognition, [5] grammar induction, [6] and information retrieval.
LLMs are pattern completion programs: They generate text by outputting the words most likely to come after the previous ones. They learn these patterns from their training data, which includes a wide variety of content from the Internet and elsewhere, including works of fiction, low-effort forum posts, unstructured and low-quality content for ...
3.3 billion words [3] 9 [4] Apache 2.0 [5] An early and influential language model. [6] Encoder-only and thus not built to be prompted or generative. [7] Training took 4 days on 64 TPUv2 chips. [8] T5: October 2019: Google 11 [9] 34 billion tokens [9] Apache 2.0 [10] Base model for many Google projects, such as Imagen. [11] XLNet: June 2019 ...
Bidirectional encoder representations from transformers (BERT) is a language model introduced in October 2018 by researchers at Google. [1] [2] It learns to represent text as a sequence of vectors using self-supervised learning.
Halyna Hutchins's final words on the set of Rust have been revealed.. The Los Angeles Times has new details of the frenzy on the Bonanza Creek Ranch movie set outside Santa Fe, New Mexico, on Oct ...
The Pile is an 886.03 GB diverse, open-source dataset of English text created as a training dataset for large language models (LLMs). It was constructed by EleutherAI in 2020 and publicly released on December 31 of that year. [1] [2] It is composed of 22 smaller datasets, including 14 new ones. [1]