Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
Anime
Illustration
Midjourney
LONGD
s6yx
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/3DRendering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/3DRendering 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/3DRendering", 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 text_encoder/pytorch_model.bin from Yntec/3DRendering: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/Yntec/3DRendering/resolve/refs%2Fpr%2F1/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Yntec/3DRendering@refs/pr/1/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Yntec/3DRendering/resolve/refs%2Fpr%2F1/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 56df0a245fd1833ab10800c430ff79ced390ab1ade3df975d12e37dbdc1affff
- Size of remote file:
- 492 MB
- SHA256:
- 678165d033be9b9e186c97f7a43aa06542dbbd0e0f07978b776f6b90df76f9b8
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