Instructions to use lwgithub/sdxl-controlnet-lora-17163 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lwgithub/sdxl-controlnet-lora-17163 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lwgithub/sdxl-controlnet-lora-17163") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-375/optimizer.bin from lwgithub/sdxl-controlnet-lora-17163: direct link, hf CLI and curl.
- Browser
- Download file 15 MB
-
https://huggingface.co/lwgithub/sdxl-controlnet-lora-17163/resolve/main/checkpoint-375/optimizer.bin
- Command line
-
hf download hf://lwgithub/sdxl-controlnet-lora-17163/checkpoint-375/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/lwgithub/sdxl-controlnet-lora-17163/resolve/main/checkpoint-375/optimizer.bin
15 MB
- Xet hash:
- 2c96fe9293e893626adb5f0a6c4981788af9ba52cbe160687bb2ef75dc7c5611
- Size of remote file:
- 15 MB
- SHA256:
- 52651889adbae663e2c944c9775f7ec630e5f2e49fcccb49f755c35e44ab41b7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.