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Aman sahu
Aman sahu
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May 14, 2023

7:48 pm


BERT and GPT models are both based on transformer architectures and are trained on large amounts of text data. However, they differ in some important ways:

  1. Training Data: BERT is trained on a combination of masked language modeling and next sentence prediction tasks, while GPT models are trained on an unsupervised language modeling task.
  2. Bidirectionality: BERT is a bidirectional model, meaning it can take into account both the left and right context of a given word when generating its representation. GPT models are unidirectional and can only consider the left context.
  3. Fine-tuning: BERT is often fine-tuned on specific downstream tasks, such as natural language understanding (NLU) or natural language generation (NLG), while GPT models are usually fine-tuned for generative language tasks.

Both BERT and GPT models are state-of-the-art language models, and the choice of which one to use depends on the specific task and the available resources.

Posted in General Knowledge
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