Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
Photorealistic
Realistic
Analog
Portrait
Semi-Realistic
stable-diffusion
stable-diffusion-diffusers
SG_161222
epinikion
Instructions to use Yntec/epiCVision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/epiCVision 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/epiCVision", 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/epiCVision: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/Yntec/epiCVision/resolve/refs%2Fpr%2F1/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Yntec/epiCVision@refs/pr/1/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Yntec/epiCVision/resolve/refs%2Fpr%2F1/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- e7fe6030036059538dbbb1470301333108d9fca0b507f617c797a3097daac186
- Size of remote file:
- 335 MB
- SHA256:
- a636481d5051b9e61e9f27753bccb1b3e0ed2ec59850173c63d76ae9d8b44b61
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