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 Annotators/UNet.pth from bdsqlsz/qinglong_controlnet-lllite: direct link, hf CLI and curl.
- Browser
- Download file 6.43 MB
-
https://huggingface.co/bdsqlsz/qinglong_controlnet-lllite/resolve/2aaba44e0714171273409aa581bf7f15491df8d3/Annotators/UNet.pth
- Command line
-
hf download hf://bdsqlsz/qinglong_controlnet-lllite@2aaba44e0714171273409aa581bf7f15491df8d3/Annotators/UNet.pth
-
curl -L -o UNet.pth https://huggingface.co/bdsqlsz/qinglong_controlnet-lllite/resolve/2aaba44e0714171273409aa581bf7f15491df8d3/Annotators/UNet.pth
6.43 MB
- Xet hash:
- 4e0f9d5d361b1fafa2285f04ede7c612c25ce79bf85cc7a72b7bdfd3ac3c4ea1
- Size of remote file:
- 6.43 MB
- SHA256:
- 96c2a509b3eb1b2083b5384bbc30808dc205f370c513ee930e644edc0ea4688d
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