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@@ -43,7 +43,7 @@ RUDOLPH 1.3B is a Transformer-based decoder model with the following parameters:
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  The primary proposed method is to modify the sparse transformer's attention mask to better control multi-modalities and up to the next level with "hyper-modality". It allows us to calculate the transitions of modalities in both directions, unlike another similar work DALL-E Transformer, which used only one direction, "text to image". The proposed "image to right text" direction is achieved by extension sparse attention mask to the right for auto-repressively text generation with both image and left text condition.
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- <img src="https://raw.githubusercontent.com/ai-forever/ru-dolph/master/pics/attention_mask_13b.png" height="20" border="2"/>
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  # Authors
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  The primary proposed method is to modify the sparse transformer's attention mask to better control multi-modalities and up to the next level with "hyper-modality". It allows us to calculate the transitions of modalities in both directions, unlike another similar work DALL-E Transformer, which used only one direction, "text to image". The proposed "image to right text" direction is achieved by extension sparse attention mask to the right for auto-repressively text generation with both image and left text condition.
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+ <img src="https://raw.githubusercontent.com/lizagonch/ru-dolph/develop_v1/pics/attention_masks_1300m.png" height="20" border="2"/>
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  # Authors
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