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:
- b4f57fad352aec1c7aa39504e6a2c57b92ab91b6cb73f096abec92d853152928
- Size of remote file:
- 681 MB
- SHA256:
- c0bb8ac4d768054c57d6e1be0ae8b2d11680461167bfb589e9d0912ab77e7103
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