Instructions to use CiroN2022/ldr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CiroN2022/ldr with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CiroN2022/ldr", 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:
- 5cb56da29a97ec30b17a84cc65419721d417ded1df819847b3ef9b0a726570b1
- Size of remote file:
- 246 MB
- SHA256:
- 464dc6b7a45269fe3a5f04149951051ab1df436fac56d63d281a6554c6404f15
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