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-0100-2599077425.png from bdsqlsz/qinglong_controlnet-lllite: direct link, hf CLI and curl.
- Browser
- Download file 4.82 MB
-
https://huggingface.co/bdsqlsz/qinglong_controlnet-lllite/resolve/main/sample/grid-0100-2599077425.png
- Command line
-
hf download hf://bdsqlsz/qinglong_controlnet-lllite/sample/grid-0100-2599077425.png
-
curl -L -o grid-0100-2599077425.png https://huggingface.co/bdsqlsz/qinglong_controlnet-lllite/resolve/main/sample/grid-0100-2599077425.png
4.82 MB

- Xet hash:
- 942a8d2d2336472ace710ea7f7665da8b3fb30cc389161000a3d53cd7817df82
- Size of remote file:
- 4.82 MB
- SHA256:
- 2c1b3b1f5921d942a797aaf7714fa5345d64e125c74331fb136708ae5b0792f9
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