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
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Download README.md from bdsqlsz/qinglong_controlnet-lllite: direct link, hf CLI and curl.
- Browser
- Download file 3.24 kB
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https://huggingface.co/bdsqlsz/qinglong_controlnet-lllite/resolve/015482893182906f5a7c12679ad754cfdccf480a/README.md
- Command line
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hf download hf://bdsqlsz/qinglong_controlnet-lllite@015482893182906f5a7c12679ad754cfdccf480a/README.md
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curl -L -o README.md https://huggingface.co/bdsqlsz/qinglong_controlnet-lllite/resolve/015482893182906f5a7c12679ad754cfdccf480a/README.md
3.24 kB
metadata
license: cc-by-nc-sa-4.0
Pre-trained models and output samples of ControlNet-LLLite form bdsqlsz
Inference with ComfyUI: https://github.com/kohya-ss/ControlNet-LLLite-ComfyUI
For 1111's Web UI, sd-webui-controlnet extension supports ControlNet-LLLite.
Training: https://github.com/kohya-ss/sd-scripts/blob/sdxl/docs/train_lllite_README.md
The recommended preprocessing for the animeface model is Anime-Face-Segmentation
Models
Trained on anime model
AnimeFaceSegment、Normal、T2i-Color/Shuffle、lineart_anime_denoise、recolor_luminance
Base Model useKohaku-XL
MLSD
Base Model useProtoVision XL - High Fidelity 3D













































