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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license: creativeml-openrail-m
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## Examples
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Below are some examples of images generated using this model:
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**Cartoon Mouse:**
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)%2C%20CharHelper_.50%2C%20digital%20%5Bpainting_illustration_.50%5D%2C%20concept%2C%20((close-up))%20portrait%2C%20character%20ar.png)
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```
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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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license: creativeml-openrail-m
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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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