Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use digiplay/DreamShaper_7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use digiplay/DreamShaper_7 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("digiplay/DreamShaper_7", 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.bin from digiplay/DreamShaper_7: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/digiplay/DreamShaper_7/resolve/refs%2Fpr%2F2/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://digiplay/DreamShaper_7@refs/pr/2/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/digiplay/DreamShaper_7/resolve/refs%2Fpr%2F2/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 3f91c8608722a3d3b59fbaed3a8e7f6c299fa99d749df1a4212165bf094ec3bc
- Size of remote file:
- 335 MB
- SHA256:
- a5734bdcf7a7a269fd10d24d4d2f2e6e635a9e67b9b64b2a18f51c74428f93da
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