Can transformers process images as well as text?
Yes. An architecture can represent image patches or other visual features as inputs to transformer processing. The input encoding and training objective differ from those of text-only models.
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No. Transformer blocks also include learned feed-forward transformations and commonly use residual connections, normalization, and position information. These components contribute to the model’s behavior together.
Encoder-only models typically build input representations using bidirectional context, while causal decoder-only models support next-token generation by restricting access to future positions in the sequence.
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