Instructions to use wavymulder/collage-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wavymulder/collage-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("wavymulder/collage-diffusion", 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 unet/diffusion_pytorch_model.bin from wavymulder/collage-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/wavymulder/collage-diffusion/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://wavymulder/collage-diffusion/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/wavymulder/collage-diffusion/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 479bbfc7142519efad4e40da088f9a049dd4c56d6459c91512047a2d55a3a3cf
- Size of remote file:
- 3.44 GB
- SHA256:
- b3fa8ceae92917f175978f83fd282522b1688dbd84c20a436e843916c550185a
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