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- ...you Need]] [[paper]]. The Transformer architecture is an example of the [[encoder-decoder models]], which had been popular for a few years. Until then, however, [[at581 bytes (85 words) - 05:30, 17 February 2023
- 4 KB (597 words) - 19:00, 18 March 2023
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- | related-to = vision-encoder-decoder, image-captioning ...-tags = Image-to-Text, PyTorch, Transformers, doi:10.57967/hf/0222, vision-encoder-decoder, image-captioning, License: apache-2.038 KB (4,971 words) - 03:33, 23 May 2023
- 18 KB (2,517 words) - 22:04, 27 May 2023
- ...ne learning models and methods rely on them internally. For instance, in [[encoder-decoder architectures]], the embeddings generated by the encoder contain the requir12 KB (1,773 words) - 17:39, 8 April 2023
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- 4 KB (542 words) - 13:11, 18 March 2023
- | '''[[HRED]]''' || || [[Hierarchical Recurrent Encoder-Decoder]] | '''[[VHRED]]''' || || [[Variational Hierarchical Recurrent Encoder-Decoder]]34 KB (4,201 words) - 04:37, 2 August 2023
- 13 KB (1,776 words) - 18:48, 17 April 2023
- 20 KB (1,948 words) - 23:18, 5 February 2024