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---
license: apache-2.0
language:
- en
---
# Penelope Palette: Portrait Generation Model
Important note : Provisory Model card mostly a placeholder.
## Model Description
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.
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 .
## Model Description
Developed by: Penelope Systems
Model type: MMDiT text-to-image generative model
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)
# License
Apache llicense 2.0
# Model Sources
For local or self-hosted use, we recommend ComfyUI for inference.
It has built-in clip so it shoul be plug & play .
ComfyUI: https://github.com/comfyanonymous/ComfyUI
# Training Dataset
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.
# Uses
Intended Uses
Intended uses include the following:
Generation of artworks and use in design and other artistic processes.
Applications in educational or creative tools.
Research on generative models, including understanding the limitations of generative models.
# Out-of-Scope Uses
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.
# Safety
Same safety measures used by Stable Diffusion 3 were deployed .
# Use recommendations :
For best use we recommand :
- steps : 32
- cfg : between 4.0 and 7.0
- sampler_name : dpmpp_2m
- scheduler : sgm_uniform
# # For best generations don't try to use realism | use words like "portrait" ; "art" ; "sketch" and so on .
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