Instructions to use martineux/fabledc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use martineux/fabledc with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("martineux/fabledc", 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:
- 1ea201042d959a9e6c9514ec0790f2ef4262afc993eea5cf740fe6f5eb69d34b
- Size of remote file:
- 167 MB
- SHA256:
- 629214263ffeaca7918383b81b9fbb3e9b9d1686409459ca3a04fe5b86d02dfc
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