Transformers Improve Language Modeling

Self-attention in Transformers allows models to predict the next word with greater context awareness.

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🤯 Did You Know (click to read)

GPT models use decoder-only Transformers to generate coherent multi-paragraph text from minimal prompts.

Unlike RNNs, which process sequences sequentially, Transformers consider all tokens simultaneously. This enables capturing long-distance dependencies, idiomatic expressions, and contextual nuances. Transformer-based language models, including GPT, achieve state-of-the-art perplexity and generation quality.

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💥 Impact (click to read)

Improved language modeling supports applications such as text generation, predictive typing, and conversational AI.

For students and developers, Transformers demonstrate the importance of context in language understanding and generation.

Source

Radford et al., 2018 - GPT

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