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-0084-938772089.png from bdsqlsz/qinglong_controlnet-lllite: direct link, hf CLI and curl.
- Browser
- Download file 6.79 MB
-
https://huggingface.co/bdsqlsz/qinglong_controlnet-lllite/resolve/main/sample/grid-0084-938772089.png
- Command line
-
hf download hf://bdsqlsz/qinglong_controlnet-lllite/sample/grid-0084-938772089.png
-
curl -L -o grid-0084-938772089.png https://huggingface.co/bdsqlsz/qinglong_controlnet-lllite/resolve/main/sample/grid-0084-938772089.png
6.79 MB

- Xet hash:
- 216cbb5833bd2f4b0c64fb5b941fe37660360dcc58e56add9f4714ad75949c5b
- Size of remote file:
- 6.79 MB
- SHA256:
- b61367b494fcf3268266d027badcb266faa3bfca793d1856d9111650d6c21bb5
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