Text-to-Image
Diffusers
StableDiffusionXLPipeline
modelslab.com
stable-diffusion-api
ultra-realistic
Instructions to use xdcx/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xdcx/model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xdcx/model", 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 xdcx/model: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/xdcx/model/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://xdcx/model/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/xdcx/model/resolve/main/vae/diffusion_pytorch_model.bin
167 MB
- Xet hash:
- 0873da44248c9bf5f76045efef9c726beedaed9ceba553bf9f45a90a11174a79
- Size of remote file:
- 167 MB
- SHA256:
- a59d7ea697f2942d22002dc3469e8c53db807a6b78f7f5ec03bd4c1f70f98efe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.