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
| license: apache-2.0 | |
| 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](https://github.com/Mikubill/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](https://github.com/siyeong0/Anime-Face-Segmentation) | |
| # Models | |
| ## Trained on anime model | |
| AnimeFaceSegment、Normal、T2i-Color/Shuffle | |
| Base Model use[Kohaku-XL](https://civitai.com/models/136389?modelVersionId=150441) | |
| MLSD | |
| Base Model use[ProtoVision XL - High Fidelity 3D](https://civitai.com/models/125703?modelVersionId=144229) | |
| # Samples | |
| ## AnimeFaceSegmentV1 | |
|   | |
|   | |
|   | |
|   | |
| ## AnimeFaceSegmentV2 | |
|  | |
|  | |
|  | |
|  | |
| ## MLSDV2 | |
| .png) | |
|  | |
|  | |
|  | |
|  | |
|  | |
| ## Normal | |
| ## T2i-Color/Shuffle |