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T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.
The company was named after the U+1F917 珞 HUGGING FACE emoji. [1] After open sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning. In March 2021, Hugging Face raised US$40 million in a Series B funding round. [2]
It was partially released in February 2019, followed by full release of the 1.5-billion-parameter model on November 5, 2019. [3] [4] [5] GPT-2 was created as a "direct scale-up" of GPT-1 [6] with a ten-fold increase in both its parameter count and the size of its training dataset. [5]
The transformer model has been implemented in standard deep learning frameworks such as TensorFlow and PyTorch. Transformers is a library produced by Hugging Face that supplies transformer-based architectures and pretrained models. [11]
In 2022, a chatbot based on GPT-3, ChatGPT, became unexpectedly popular, [36] triggering a boom around large language models. [37] [38] Since 2020, Transformers have been applied in modalities beyond text, including the vision transformer, [39] speech recognition, [40] robotics, [41] and multimodal. [42]
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.
A chatbot is a software application or web interface that is designed to mimic human conversation through text or voice interactions. [1] [2] [3] Modern chatbots are typically online and use generative artificial intelligence systems that are capable of maintaining a conversation with a user in natural language and simulating the way a human would behave as a conversational partner.
Shannon's diagram of a general communications system, showing the process by which a message sent becomes the message received (possibly corrupted by noise). seq2seq is an approach to machine translation (or more generally, sequence transduction) with roots in information theory, where communication is understood as an encode-transmit-decode process, and machine translation can be studied as a ...