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What Is a Transformer?
The architecture behind modern language models.
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AiTechWorlds
AiTechWorlds
Transformers are the neural network architecture behind modern AI like ChatGPT. This visual guide explains attention, self-attention, encoders and decoders, positional encoding, and why transformers replaced RNNs for language and beyond.
The architecture behind modern language models.
They power ChatGPT, translation, and more.
RNNs are slow and forget long context.
Transformers handle whole sequences at once.
Focus on the most relevant parts of the input.
Each word relates to every other word.
The mechanism that computes attention.
How much each token attends to others.
Look at relationships from many angles.
Adds order since there’s no recurrence.
Understands the input sequence.
Generates the output sequence.
Great for translation tasks.
Power generative LLMs like GPT.
Process attention outputs further.
Stabilizes deep training.
More data and parameters improve results.
Transformers now handle vision and audio.
The 2017 paper that started it all.
Use a pretrained transformer via Hugging Face.
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