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
Add pipeline tag
Browse filesThis PR ensures the model can be found at https://huggingface.co/models?pipeline_tag=text-to-image&sort=trending.
README.md
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language:
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- en
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library_name: diffusers
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---
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<div align="center">
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<h1>StoryMaker: Towards consistent characters in text-to-image generation</h1>
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language:
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- en
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library_name: diffusers
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pipeline_tag: text-to-image
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---
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<div align="center">
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<h1>StoryMaker: Towards consistent characters in text-to-image generation</h1>
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