Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
Photorealistic
Realism
Girls
epinikion
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/epiCPhotoGasm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/epiCPhotoGasm 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/epiCPhotoGasm", 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/epiCPhotoGasm: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/Yntec/epiCPhotoGasm/resolve/refs%2Fpr%2F2/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Yntec/epiCPhotoGasm@refs/pr/2/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Yntec/epiCPhotoGasm/resolve/refs%2Fpr%2F2/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- b396c724e8bf62620235756ad838d45e1769e25e57c99a356ac596399ebcf479
- Size of remote file:
- 335 MB
- SHA256:
- 5d992aa60e6dd535cc8f9e56c1c2b8f7ea286acec0c90f092b76de97f9442f32
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