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:
- 4cf4686a9a6f8a3ffa55cfdc1cb43bc4640e57ec8c42b6f326bd2fa6b4a34bef
- Size of remote file:
- 3.89 MB
- SHA256:
- 1677a9fb5b6a4162578dc677a1fc3015755d5bd6de4d8d535daed5ac71e3cd07
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