Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
General
Anime
Art
Girl
Photorealistic
LandScapes
Lykon
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/DreamShaperRemix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/DreamShaperRemix with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/DreamShaperRemix", 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 Yntec/DreamShaperRemix: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/Yntec/DreamShaperRemix/resolve/refs%2Fpr%2F3/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Yntec/DreamShaperRemix@refs/pr/3/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Yntec/DreamShaperRemix/resolve/refs%2Fpr%2F3/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 183ab69ea47b26b3449c3e52f12a280cf92ac5a0023e2ec93bb70264ab11bb9c
- Size of remote file:
- 335 MB
- SHA256:
- c03519403f1fea9a3901a3aba2d935663eb34ba060d48a64e1528a36f32ef54a
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