Instructions to use mirroring/civitai_mirror with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mirroring/civitai_mirror with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mirroring/civitai_mirror", 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:
- 514db3f48f7dbcc4e6cc43355ff7d8045e985d00681206c042d2548d5ac9cc61
- Size of remote file:
- 59.2 kB
- SHA256:
- bd9b9dcf8b30aa2787f51c3346fd9e3c0447b4bfb0d26fd4f0247dfd15f9b646
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.