Instructions to use furusu/th-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use furusu/th-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("furusu/th-diffusion", 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
- Draw Things
- DiffusionBee

- Xet hash:
- d5563f68a8d09cf8012d60862bda703bdc9b572301fffa14e3555efdfab5e735
- Size of remote file:
- 3.56 MB
- SHA256:
- a984fec2f166630566d38175ceb5a2e5493ab0ca22811fa0fe074f477d2087ea
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