Instructions to use LYAWWH/DreamLight with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LYAWWH/DreamLight with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LYAWWH/DreamLight", torch_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
- Xet hash:
- 863775117d62c86d914bd77ea5e9e305566dd3b39ce5e62f8120fa24c17512f3
- Size of remote file:
- 5.06 GB
- SHA256:
- b9e6c65d9a3576bf1475824db1325deb63d7c166150cd867b329cbd22ba6de84
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