Instructions to use Falah/islamicdiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Falah/islamicdiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Falah/islamicdiffusion", 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
- Draw Things
- DiffusionBee
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README.md
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### islamicdiffusion Dreambooth model trained by Falah
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Test the concept via A1111 Colab [fast-Colab-A1111](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb)
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Sample pictures of this concept with simple and easy
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any prompt and add word islamidiffusion style :
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### islamicdiffusion Dreambooth model trained by Falah
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With Stable Diffusion DreamBooth, we can now create AI art generation images using our own trained images.
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in this model, we can generate images with Islamic landscapes or female or male ones as popular images or just about anything you can think of
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Test the concept via A1111 Colab [fast-Colab-A1111](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb)
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Sample pictures of this concept with the simple and easy prompts:
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any prompt and add word islamidiffusion style :
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