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@@ -39,6 +39,9 @@ The model is trained on images and content from the following sources:
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  These datasets may not cover all possible themes or subjects comprehensively. The dataset may lack representation of certain modern or niche topics due to the limited availability of such content under these licenses. Additionally, the model was trained and developed with a focus on compliance with the Brazilian Copyright Act, which imposes stricter regulations compared to other jurisdictions due to the absence of fair use provisions.
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  ## Associated Risks
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  * The model might struggle with generating highly detailed text within images.
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  * There may be limitations in creating complex scenes that require deep compositional understanding.
 
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  These datasets may not cover all possible themes or subjects comprehensively. The dataset may lack representation of certain modern or niche topics due to the limited availability of such content under these licenses. Additionally, the model was trained and developed with a focus on compliance with the Brazilian Copyright Act, which imposes stricter regulations compared to other jurisdictions due to the absence of fair use provisions.
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+ It is important to note that while every effort has been made to ensure the model generates ethical and high-quality content, it is not possible to guarantee that the model will always avoid producing unwanted content or achieve the highest quality in every instance. This project represents an attempt to create an ethical model within the constraints of the available datasets and legal considerations.
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+ Copyright laws differ from country to country, and this project acknowledges the necessity of establishing guidelines for considering public domain content. It is hoped that this research will inspire others to build more responsible models, taking into account the complexities of copyright laws and the ethical use of training data.
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  ## Associated Risks
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  * The model might struggle with generating highly detailed text within images.
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  * There may be limitations in creating complex scenes that require deep compositional understanding.