Instructions to use percool/sdxl-lora-testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use percool/sdxl-lora-testing 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("percool/sdxl-lora-testing") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-2000/optimizer.bin from percool/sdxl-lora-testing: direct link, hf CLI and curl.
- Browser
- Download file 60.3 MB
-
https://huggingface.co/percool/sdxl-lora-testing/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://percool/sdxl-lora-testing/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/percool/sdxl-lora-testing/resolve/main/checkpoint-2000/optimizer.bin
60.3 MB
- Xet hash:
- c03bdf435b3a7d085d95c7491c77a359d101943ecc469659a56c7b33f66ebaf4
- Size of remote file:
- 60.3 MB
- SHA256:
- 5cc68fff0c8c241af9fc0bb5698e0fb28e70c6f444b8a1c23b4f97cc3d7d2214
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.