GPT-2
2019 text-generating large language model
Nº Q95726727 ★★
Uncommon · Literature
GPT-2
2019 text-generating large language model
Generative Pre-trained Transformer 2 (GPT-2) is a large language model (LLM) by OpenAI and the second in their foundational series of GPT models. GPT-2 was pre-trained on a dataset of 8 million web pages.
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From Wikipedia
Generative Pre-trained Transformer 2 (GPT-2) is a large language model (LLM) by OpenAI and the second in their foundational series of GPT models. GPT-2 was pre-trained on a dataset of 8 million web pages. It was partially released in February 2019, followed by full release of the 1.5-billion-parameter model on November 5, 2019. GPT-2 was created as a "direct scale-up" of GPT-1 with a ten-fold increase in both its parameter count and the size of its training dataset. It is a general-purpose learner and its ability to perform the various tasks was a consequence of its general ability to accurately predict the next item in a sequence, which enabled it to translate texts, answer questions about a topic from a text, summarize passages from a larger text, and generate text output on a level sometimes indistinguishable from that of humans; however, it could become repetitive or nonsensical when generating long passages. It was superseded by the GPT-3 and GPT-4 models, which are no longer open source. GPT-2 has, like its predecessor GPT-1 and its successors GPT-3, GPT-4 and GPT-5, a generative pre-trained transformer architecture, implementing a deep neural network, specifically a transformer model, which uses attention instead of older recurrence- and convolution-based architectures. Attention mechanisms allow the model to selectively focus on segments of input text it predicts to be the most relevant. This model allows for greatly increased parallelization, and outperforms previous benchmarks for RNN/CNN/LSTM-based models.
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