Instructions to use 004T/StableXlL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 004T/StableXlL with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("004T/StableXlL", 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.bin from 004T/StableXlL: direct link, hf CLI and curl.
- Browser
- Download file 4.91 GB
-
https://huggingface.co/004T/StableXlL/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://004T/StableXlL/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/004T/StableXlL/resolve/main/unet/diffusion_pytorch_model.bin
4.91 GB
- Xet hash:
- 4326a8e418f5977c4cf0f84efadcd51a24d23ade9a0dc9ef70c8a971fa3bc038
- Size of remote file:
- 4.91 GB
- SHA256:
- bf4c63c68860933264eaa290f7f9e308ce5d69a8a3012c26822de98aa056ab30
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