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🤯 Did You Know (click to read)
GPT-3, with 175 billion parameters, demonstrates how scaling Transformers improves context understanding and generative quality.
GPT uses stacked Transformer decoder layers to generate text autoregressively. Self-attention allows the model to consider prior tokens, maintaining coherence over long sequences. Large-scale pretraining captures diverse language patterns, enabling versatile generation for dialogue, summarization, and creative writing.
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💥 Impact (click to read)
Text generation with Transformers enables chatbots, content creation, and AI-assisted writing applications.
Students, researchers, and developers can experiment with AI-generated text for learning, prototyping, and creative exploration.
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