Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
sadxzero
Instructions to use Yntec/Luma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/Luma 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/Luma", 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
- Xet hash:
- 016192bf21191a05232309314fe9f6f74f5ac78e62281cd9e8c72f79e2d61a27
- Size of remote file:
- 1.72 GB
- SHA256:
- 1f374c2c85ee32b7bf54fa03135eefc4c88dd1a4605b6b37322f48dc9162dc36
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