Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
General
Anime
Art
Girl
Photorealistic
3D
LandScapes
stable-diffusion
stable-diffusion-diffusers
XpucT
Lykon
Instructions to use Yntec/DeliShaper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/DeliShaper 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/DeliShaper", 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 Yntec/DeliShaper: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/Yntec/DeliShaper/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Yntec/DeliShaper/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Yntec/DeliShaper/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 96b12b24c9b1bfabea8c005e5c1818d05485338172688635c7650c489cc6b1d3
- Size of remote file:
- 3.44 GB
- SHA256:
- cb67656ed554ee7981505d5aec34337857e8d203c8ce353af9601d3c96663389
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