Instructions to use Dipl0/pepe-diffuser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Dipl0/pepe-diffuser with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Dipl0/pepe-diffuser", 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:
- 12c3a12199046fa0b2ac903293a3e43392a85214e13e7190db287aada3e931bd
- Size of remote file:
- 3.46 GB
- SHA256:
- c7cacf554de4cf0efa56b83e91c1cf6d63b4314633b206e502507e6cfa4e3335
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