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+ # Emojich
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+ ![](./pics/emojich_rgba_100.png)
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+ ### generate emojis from text
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+ Model was trained by [Sber AI](https://github.com/sberbank-ai)
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+ * Task: `text2image generation`
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+ * Num Parameters: `1.3 B`
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+ * Training Data Volume: `120 million text-image pairs` & [`2749 text-emoji pairs`](https://www.kaggle.com/shonenkov/russian-emoji)
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+ ### Model Description
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+ 😋 Emojich is a 1.3 billion params model from the family GPT3-like, it generates emoji-style images with the brain of ◾ Malevich.
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+ ### Fine-tuning stage:
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+ The main goal of fine-tuning is trying to keep the generalization of [ruDALL-E Malevich (XL)](https://huggingface.co/sberbank-ai/rudalle-Malevich)
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+ model on text to emoji tasks. ruDALL-E Malevich is a multi-modality big pretrained transformer, that uses images and texts.
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+ The idea with freezing feedforward and self-attention layers in pretrained transformer is demonstrated high performance in changing different modalities.
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+ Also, the model has a good chance for over-fitting text modality and lost generalization.
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+ To deal with this problem is increased coefficient 10^3 in weighted cross-entropy loss for image codebooks part.
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+ Full version of code is available on Kaggle [here](https://www.kaggle.com/shonenkov/emojich-rudall-e).
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+ ### Examples of generated emojis
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+ ![](./pics/examples.png)
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