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OpenAI's GPT-n series Model Architecture Parameter count Training data Release date Training cost GPT-1: 12-level, 12-headed Transformer decoder (no encoder), followed by linear-softmax. 117 million BookCorpus: [39] 4.5 GB of text, from 7,000 unpublished books of various genres. June 11, 2018 [9] 30 days on 8 P600 graphics cards, or 1 petaFLOPS ...
It uses advanced artificial intelligence (AI) models called generative pre-trained transformers (GPT), such as GPT-4o, to generate text. GPT models are large language models that are pre-trained to predict the next token in large amounts of text (a token usually corresponds to a word, subword or punctuation). This pre-training enables them to ...
However, an average word in another language encoded by such an English-optimized tokenizer is split into a suboptimal amount of tokens. GPT-2 tokenizer can use up to 15 times more tokens per word for some languages, for example for the Shan language from Myanmar. Even more widespread languages such as Portuguese and German have "a premium of ...
GPT-4o ("o" for "omni") is a multilingual, multimodal generative pre-trained transformer developed by OpenAI and released in May 2024. [1] GPT-4o is free, but ChatGPT Plus subscribers have higher usage limits. [ 2 ]
The upshot is that the 79 million words in fact span the 239,000 bona fide articles, the remaining 22,000 linked articles, and the unknown number of articles without links. As of October 2004, the total word count in the latter two categories was estimated at two million words. Dividing the remaining 77 million words by 239,000 gives a mean ...
GPT-3 was used by The Guardian to write an article about AI being harmless to human beings. It was fed some ideas and produced eight different essays, which were ultimately merged into one article. [44] GPT-3 was used in AI Dungeon, which generates text-based adventure games. Later it was replaced by a competing model after OpenAI changed their ...
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GPT-2 was pre-trained on a dataset of 8 million web pages. [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]
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