ChatGPT is powered by a transformer-based model, which processes text data in a hierarchical and parallel manner. Here’s how ChatGPT works:
ChatGPT is pre-trained on a diverse corpus of text data to learn language patterns, grammar rules, and context. This step helps the model understand the nuances of human language.
After pre-training, ChatGPT can be fine-tuned on specific datasets or tasks to improve performance. Fine-tuning adapts the model to a particular domain or application.
During inference, ChatGPT takes an input text prompt and generates a response using the learned patterns and context. The model predicts the most probable next words based on the input sequence.
ChatGPT generates responses by sampling from the probability distribution of the next word. The model prioritizes words that are more likely to occur in a given context, resulting in coherent and contextually relevant responses.
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