Instructions to use clem/friedeberg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use clem/friedeberg with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("clem/friedeberg", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- f3e325a1893ae0db44aeeaa35d768c56d4cfe231f0b265b9da0a201d57f83ff4
- Size of remote file:
- 3.46 GB
- SHA256:
- 8218c979b22e25cd57ab268f91797dc8e4883737ca36a926afcaf38695c7bc16
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