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.fp16.bin from Yntec/DeliShaper: direct link, hf CLI and curl.
- Browser
- Download file 1.72 GB
-
https://huggingface.co/Yntec/DeliShaper/resolve/main/unet/diffusion_pytorch_model.fp16.bin
- Command line
-
hf download hf://Yntec/DeliShaper/unet/diffusion_pytorch_model.fp16.bin
-
curl -L -o diffusion_pytorch_model.fp16.bin https://huggingface.co/Yntec/DeliShaper/resolve/main/unet/diffusion_pytorch_model.fp16.bin
1.72 GB
- Xet hash:
- 212e09dc8e8bf421dfb3b7bc9c0b84b4d1830af0c886d028476ca57740faf643
- Size of remote file:
- 1.72 GB
- SHA256:
- ef450e47b86a7ccc6dd91e2cf44fcc549cf4aca58d32680286be6981f63fec70
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