Instructions to use OlafII/cosmosx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OlafII/cosmosx with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OlafII/cosmosx", 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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Use in prompt: "cosmosx"
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Trained on Stable Diffusion v1.5 using ShivamShrirao Dreambooth
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# Cosmosx is a fine tuned Stable Diffusion model trained on high quality star constellation images
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Use in prompt: "cosmosx"
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Trained on Stable Diffusion v1.5 using ShivamShrirao Dreambooth
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