Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use kabachuha/gigafractal2-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kabachuha/gigafractal2-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kabachuha/gigafractal2-diffusion", 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 gradio demo badge
#2
by akhaliq HF Staff - opened
README.md
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Gigafractal2 Diffusion is a latent text-to-image diffusion model based on the original StabilityAI Stable Diffusion v2.0 and then fine-tuned on 40 images origanally made with another diffusion model named 'Disco Diffusion' using Dreambooth. This model has been created to explore the possibilities and limitations of Dreambooth training with training steps increased much more than usual and to overcome biases in the model created by the text incoder's token associations. The purpose of this model is to provide the biomorphic fractalism effect present in Disco Diffusion, but without the bias to 'Disco parties' and especially 'discoballs' for which [the model by snek](was known for).
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To use this style in your generations, add `gigafractal artstyle` to the prompts.
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# Gradio
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We support a [Gradio](https://github.com/gradio-app/gradio) Web UI to run gigafractal2-diffusion:
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[](https://huggingface.co/spaces/akhaliq/gigafractal2-diffusion)
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Gigafractal2 Diffusion is a latent text-to-image diffusion model based on the original StabilityAI Stable Diffusion v2.0 and then fine-tuned on 40 images origanally made with another diffusion model named 'Disco Diffusion' using Dreambooth. This model has been created to explore the possibilities and limitations of Dreambooth training with training steps increased much more than usual and to overcome biases in the model created by the text incoder's token associations. The purpose of this model is to provide the biomorphic fractalism effect present in Disco Diffusion, but without the bias to 'Disco parties' and especially 'discoballs' for which [the model by snek](was known for).
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To use this style in your generations, add `gigafractal artstyle` to the prompts.
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