Text-to-Image
Diffusers
diffusers-training
lora
template:sd-lora
stable-diffusion-xl
stable-diffusion-xl-diffusers
Instructions to use nityanandmathur/cityscapes-sdxl-lora-r4-i1000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nityanandmathur/cityscapes-sdxl-lora-r4-i1000 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("nityanandmathur/cityscapes-sdxl-lora-r4-i1000") prompt = "a car in sks scene" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- 32795cde16a9b361aa8d7a4f8372b6d0d149e10fa4880cb7b3008e1a4a438d56
- Size of remote file:
- 1.22 MB
- SHA256:
- 27c512b1ea9320a9bdfd9a209e8675e15792ed4b9ff1606fe09e7110e87840cc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.