Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
Realism
Splash,
Explosion
Jehovah
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/Splash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/Splash 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/Splash", 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/Splash: direct link, hf CLI and curl.
- Browser
- Download file 1.72 GB
-
https://huggingface.co/Yntec/Splash/resolve/refs%2Fpr%2F1/unet/diffusion_pytorch_model.fp16.bin
- Command line
-
hf download hf://Yntec/Splash@refs/pr/1/unet/diffusion_pytorch_model.fp16.bin
-
curl -L -o diffusion_pytorch_model.fp16.bin https://huggingface.co/Yntec/Splash/resolve/refs%2Fpr%2F1/unet/diffusion_pytorch_model.fp16.bin
1.72 GB
- Xet hash:
- 7c5f56a4703b909de563b04575b1518141e604708931b1440c527901dab69220
- Size of remote file:
- 1.72 GB
- SHA256:
- 240f33e8c8a03f1f63d819bf8abc0249b15e4b5d52020a41bff819be78f2c3b8
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