File:CRAIYON-Teddy bears working on new AI research underwater with 1990s technology.jpg
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CRAIYON-Teddy_bears_working_on_new_AI_research_underwater_with_1990s_technology.jpg (256 × 256 pixels, file size: 16 KB, MIME type: image/jpeg)
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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. |
Source | craiyon.com |
Author | Craiyon |
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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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current | 15:53, 27 July 2022 | 256 × 256 (16 KB) | JPxG (talk | contribs) | == {{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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