Instructions to use ECarbenia/grimoiresigils with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ECarbenia/grimoiresigils with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ECarbenia/grimoiresigils", 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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Results are generally black and white, unlike models which are not trained on this dataset.
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Special care has been taken to include multiple traditions, and spirits corresponding to each element, zodiac, direction, tree of life sphere, etc. in roughly equal parts.
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### grimoiresigils Dreambooth model trained by ECarbenia with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
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Results are generally black and white, unlike models which are not trained on this dataset.
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Special care has been taken to include multiple traditions, and spirits corresponding to each element, zodiac, direction, tree of life sphere, etc. in roughly equal parts.
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Be sure to include the word "sigil" in the prompt. The prompt can be strengthened by including the term "grimoiresigils" as well.
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### grimoiresigils Dreambooth model trained by ECarbenia with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
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