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 text_encoder/pytorch_model.bin from xdcx/model: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/xdcx/model/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://xdcx/model/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/xdcx/model/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- ad694e5ad982412d5d8eb612f479f042d9a2bad1fad42ecd343c2c5a914bf5fe
- Size of remote file:
- 246 MB
- SHA256:
- 2c483d4b605f63e93d4ce1b5db4e117b6e167d2c2e8839e7d607cda7d66ba23c
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