Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
Ultra Detailed
Ultra Realistic
Ultra Versatile
Photographic
Cinematic
artificialguybr
LEOSAM
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/UltraHighDefinition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/UltraHighDefinition with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/UltraHighDefinition", 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
Update README.md
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README.md
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Sometimes I just sit generating many samples for models, I think this one deserves it.
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Samples and prompts (keep
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Sometimes I just sit generating many samples for models, I think this one deserves it.
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Samples and prompts (keep scrolling to see more):
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Top left: Baby girl with a giant basket full of grapes, high quality, grass by wess anderson
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Top right: A high contrast portrait of a happy fuzzy panda bear dressed as a chef in a high end kitchen making dough. There is a painting of flowers on the wall behind
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Bottom left: 60's interiors of an apartment, photorealistic, cinematic, volume light, rendered in octane, artstation
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Bottom right: a pretty cute little girl with curly ponytail hair, detailed face, bow, holding her tennis gameboy up, northern sky, walking by the city, blue sky, vast clouds
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