Instructions to use RED-AIGC/StoryMaker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RED-AIGC/StoryMaker with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RED-AIGC/StoryMaker", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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README.md
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<h1>StoryMaker: Towards consistent characters in text-to-image generation</h1>
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<a href='https://arxiv.org/pdf/2409.12576'><img src='https://img.shields.io/badge/Technique-Report-red'></a>
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</div>
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StoryMaker is a personalization solution preserves not only the consistency of faces but also clothing, hairstyles and bodies in the multiple characters scene, enabling the potential to make a story consisting of a series of images.
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<h1>StoryMaker: Towards consistent characters in text-to-image generation</h1>
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<a href='https://arxiv.org/pdf/2409.12576'><img src='https://img.shields.io/badge/Technique-Report-red'></a>
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[](https://github.com/RedAIGC/StoryMaker)
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</div>
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StoryMaker is a personalization solution preserves not only the consistency of faces but also clothing, hairstyles and bodies in the multiple characters scene, enabling the potential to make a story consisting of a series of images.
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