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-2500/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-2500/optimizer.bin
- Command line
-
hf download hf://percool/sdxl-lora-testing/checkpoint-2500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/percool/sdxl-lora-testing/resolve/main/checkpoint-2500/optimizer.bin
60.3 MB
- Xet hash:
- 9e35ca616927787046caab6d8ba7af2794d3a9ad44836f6d548681d0d23c490c
- Size of remote file:
- 60.3 MB
- SHA256:
- 9366c4ce27a1398bf9b4d5f7e0dee965d1907747745745d3e11ff47e309b2dec
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