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", torch_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:
- b003c370651dc4eef8dd1022ccfff05f6477c6b06330b2ed49e491055b39d51e
- Size of remote file:
- 3.46 GB
- SHA256:
- 186bbea7e8211c40190675b8a6eb3b330f48837e30c845c8afa22c08593c4b80
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