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:
- a2b6028023b181c6ad7d6e77ee413a039d31e854947307eadf7bcd3b6618ee8d
- Size of remote file:
- 3.3 MB
- SHA256:
- 659364cc219117c5a9d1d96a84ac180def0db8e8b3720a3e0fe99caf291ed177
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