Instructions to use bdsqlsz/qinglong_controlnet-lllite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bdsqlsz/qinglong_controlnet-lllite with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("bdsqlsz/qinglong_controlnet-lllite", 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
Download sample/grid-0000-656896882.png from bdsqlsz/qinglong_controlnet-lllite: direct link, hf CLI and curl.
- Browser
- Download file 7.4 MB
-
https://huggingface.co/bdsqlsz/qinglong_controlnet-lllite/resolve/main/sample/grid-0000-656896882.png
- Command line
-
hf download hf://bdsqlsz/qinglong_controlnet-lllite/sample/grid-0000-656896882.png
-
curl -L -o grid-0000-656896882.png https://huggingface.co/bdsqlsz/qinglong_controlnet-lllite/resolve/main/sample/grid-0000-656896882.png
7.4 MB

- Xet hash:
- 982eceb16ad764570339ed3ec462db7a8303963feaa1e90bad37c0922f31d22f
- Size of remote file:
- 7.4 MB
- SHA256:
- 65483acda02a92e8798df668bd00cdaa07dc48cf65301a18945e14d41bfd841d
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