Instructions to use cgldo/diffusionclone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cgldo/diffusionclone with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cgldo/diffusionclone", 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 vae/diffusion_pytorch_model.safetensors from cgldo/diffusionclone: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/cgldo/diffusionclone/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://cgldo/diffusionclone/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/cgldo/diffusionclone/resolve/main/vae/diffusion_pytorch_model.safetensors
335 MB
- Xet hash:
- 30e09c60cdb2fc1dadcbd1743228ebffbcae1fe4a56a5276c976ea36eb8ae2b5
- Size of remote file:
- 335 MB
- SHA256:
- a1d993488569e928462932c8c38a0760b874d166399b14414135bd9c42df5815
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