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-0002-1006844163.png from bdsqlsz/qinglong_controlnet-lllite: direct link, hf CLI and curl.
- Browser
- Download file 10.6 MB
-
https://huggingface.co/bdsqlsz/qinglong_controlnet-lllite/resolve/main/sample/grid-0002-1006844163.png
- Command line
-
hf download hf://bdsqlsz/qinglong_controlnet-lllite/sample/grid-0002-1006844163.png
-
curl -L -o grid-0002-1006844163.png https://huggingface.co/bdsqlsz/qinglong_controlnet-lllite/resolve/main/sample/grid-0002-1006844163.png
10.6 MB
- Xet hash:
- 75f4f4784507d12b5d1f4da69958dc342d7cb5105438d99a2ee77baec582b9e8
- Size of remote file:
- 10.6 MB
- SHA256:
- dbb3fe17cc00c04f06225a2994d07dee2014382a9a7d3c3b227a79f5904e21de
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