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
Download models/VAE/rmada-cold-vae.ckpt from mirroring/civitai_mirror: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/mirroring/civitai_mirror/resolve/main/models/VAE/rmada-cold-vae.ckpt
- Command line
-
hf download hf://mirroring/civitai_mirror/models/VAE/rmada-cold-vae.ckpt
-
curl -L -o rmada-cold-vae.ckpt https://huggingface.co/mirroring/civitai_mirror/resolve/main/models/VAE/rmada-cold-vae.ckpt
335 MB
- Xet hash:
- 336690263b4327cf152a49d5fa4d56d80cb6e73db1a1d570c4624557374bbce5
- Size of remote file:
- 335 MB
- SHA256:
- ac047f521ae1acc35abbdfa746bc3bb898f0ff7a70e619112c24dc9032f2fa05
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