Instructions to use ManglerFTW/CharHelper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ManglerFTW/CharHelper with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ManglerFTW/CharHelper", 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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<b>V1:</b>
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Trained on SD v2.1 using TheLastBen's Fast Dreambooth. This model was trained on a digital painting style mainly with characters and portraits. The main objective is to train a model to be a tool to help with character design ideas.
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Usage:
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Use CharHelper in prompt to bring out the style. Other prompts that work well are 'Character Art', 'Close-up/Mid-range Character portrait', 'Digital Painting', Digital Illustration', 'Stylized', and 'anime'.
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<b>V1:</b>
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Trained for 3500 steps on SD v2.1 using TheLastBen's Fast Dreambooth. This model was trained on a digital painting style mainly with characters and portraits. The main objective is to train a model to be a tool to help with character design ideas.
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Usage:
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Use CharHelper in prompt to bring out the style. Other prompts that work well are 'Character Art', 'Close-up/Mid-range Character portrait', 'Digital Painting', Digital Illustration', 'Stylized', and 'anime'.
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