Instructions to use dydsa/denoiser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dydsa/denoiser with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dydsa/denoiser", 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:
- 57d959ccef5df067e058166decee5711a20ca52c17dfe1ae10c5f5540baca510
- Size of remote file:
- 3.44 GB
- SHA256:
- b886ca1ff6ec1dad16865c96404c50ea73ffd057b86aeb33a218dfef5da4f454
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