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--- |
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license: apache-2.0 |
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language: |
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- en |
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--- |
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# Penelope Palette: Portrait Generation Model |
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Important note : Provisory Model card mostly a placeholder. |
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## Model Description |
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Penelope Palette is an advanced AI model designed for creating lifelike portraits. It leverages the same architecture as Stable Diffusion 3, ensuring high-quality image generation with remarkable detail and style. Most of the description was copied from the stable diffusion 3 since the informations remains generally the same. |
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The model is weaker than Stable Diffusion 3 medium , having trouble generating realistic content ; nudity and anatomy but it performs really good in portraits , having a unique style . |
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## Model Description |
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Developed by: Penelope Systems |
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Model type: MMDiT text-to-image generative model |
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Model Description: This is a model that can be used to generate images based on text prompts. It is a Multimodal Diffusion Transformer (https://arxiv.org/abs/2403.03206) that uses three fixed, pretrained text encoders (OpenCLIP-ViT/G, CLIP-ViT/L and T5-xxl) |
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# License |
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Apache llicense 2.0 |
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# Model Sources |
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For local or self-hosted use, we recommend ComfyUI for inference. |
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It has built-in clip so it shoul be plug & play . |
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ComfyUI: https://github.com/comfyanonymous/ComfyUI |
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# Training Dataset |
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We used synthetic data and filtered publicly available data to train our models. The model was pre-trained on 1 billion images. The fine-tuning data includes 30M high-quality aesthetic images focused on specific visual content and style, as well as 3M preference data images. |
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# Uses |
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Intended Uses |
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Intended uses include the following: |
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Generation of artworks and use in design and other artistic processes. |
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Applications in educational or creative tools. |
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Research on generative models, including understanding the limitations of generative models. |
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# Out-of-Scope Uses |
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The model was not trained to be factual or true representations of people or events. As such, using the model to generate such content is out-of-scope of the abilities of this model. |
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# Safety |
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Same safety measures used by Stable Diffusion 3 were deployed . |
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# Use recommendations : |
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For best use we recommand : |
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- steps : 32 |
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- cfg : between 4.0 and 7.0 |
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- sampler_name : dpmpp_2m |
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- scheduler : sgm_uniform |
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# # For best generations don't try to use realism | use words like "portrait" ; "art" ; "sketch" and so on . |
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