Instructions to use yulet1de/nitro-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yulet1de/nitro-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("yulet1de/nitro-diffusion", 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

- Xet hash:
- b56472bc9a6fc2a17f768d11ac78d7c31f51422b0d28698f7e390e0bbdfd4d46
- Size of remote file:
- 3.08 MB
- SHA256:
- d2e0daa06a2bee95c0bc1f91c74383499577531efe5204daa4ad416abc72c075
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