Instructions to use diffusers/tiny-torch-full-checker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/tiny-torch-full-checker with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers/tiny-torch-full-checker", 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:
- c52e567881a7bea6e565f82bb46338f085c947178b38151cbf99bbc59d5d6da1
- Size of remote file:
- 5.83 MB
- SHA256:
- 310d008ebe83d315e131b6ba9f24a661a0a4d6ae9d32b1d53ca4df75ff8afb6b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.