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-0030-1612754720.png from bdsqlsz/qinglong_controlnet-lllite: direct link, hf CLI and curl.
- Browser
- Download file 5.75 MB
-
https://huggingface.co/bdsqlsz/qinglong_controlnet-lllite/resolve/main/sample/grid-0030-1612754720.png
- Command line
-
hf download hf://bdsqlsz/qinglong_controlnet-lllite/sample/grid-0030-1612754720.png
-
curl -L -o grid-0030-1612754720.png https://huggingface.co/bdsqlsz/qinglong_controlnet-lllite/resolve/main/sample/grid-0030-1612754720.png
5.75 MB

- Xet hash:
- dc18ba37ecfb7a92831d4105b782336491a10f40acbfd903d793d38bd7a1a953
- Size of remote file:
- 5.75 MB
- SHA256:
- 84739d28759beae7983fd5b63ed8c6bc7c378675b6f73a7ae7052f49bf11a37f
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