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Summary
DescriptionCRAIYON-Teddy bears working on new AI research underwater with 1990s technology.jpg
Output of Craiyon (formerly "DALL-E Mini"). See the model card for information on the model used. Specifically (from the title card): "Images are encoded through a VQGAN encoder, which turns images into a sequence of tokens. Descriptions are encoded through a BART encoder. The output of the BART encoder and encoded images are fed through the BART decoder, which is an auto-regressive model whose goal is to predict the next token. Loss is the softmax cross-entropy between the model prediction logits and the actual image encodings from the VQGAN." Upscaled using Real-ESRGAN. Compare to DALL-E 2 equivalent.
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craiyon.com
Author
Craiyon
Permission (Reusing this file)
Public domain
Licensing
Public domainPublic domainfalsefalse
This file is in the public domain because it is the work of a computer algorithm or artificial intelligence and does not contain sufficient human authorship to support a copyright claim.
The United Kingdom and Hong Kong provides a limited term of copyright protection for computer-generated works of 50 years from creation. [1] [2]
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AI-generated image
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artificial intelligence art
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image/jpeg
checksum
a60af4cd0f05a2e133d54152824b6799242213eb
determination method: SHA-1
data size
16,883 byte
height
256 pixel
width
256 pixel
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15:53, 27 July 2022
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== {{int:filedesc}} == {{Information |Description=Output of Craiyon (formerly "DALL-E Mini"). See [https://huggingface.co/dalle-mini/dalle-mini the model card] for information on the model used. Specifically (from the title card): "Images are encoded through a VQGAN encoder, which turns images into a sequence of tokens. Descriptions are encoded through a BART encoder. The output of the BART encoder and encoded images are fed through the BART decoder, which is an auto-regressive model whose go...
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