Instructions to use freQuensy23/diffusion-cloody with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use freQuensy23/diffusion-cloody with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("freQuensy23/diffusion-cloody", dtype=torch.bfloat16, device_map="cuda") prompt = "A [V] cat swimming" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 8ba4550fc77b0e92f5b0999d6a65f8f8f68d6fbad39fd36e188dc2f597c07306
- Size of remote file:
- 520 Bytes
- SHA256:
- 6f638fb9401a6d6296feff533ee7efe657b787c49f954f82f5906b36ef2a1b1f
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