Instructions to use backnotprop/np_cr_model4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use backnotprop/np_cr_model4 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("backnotprop/np_cr_model4") prompt = "spiral wave flower,minimalism,white_background,abstract,photoshop generated abstract on a white background" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download image_1.png from backnotprop/np_cr_model4: direct link, hf CLI and curl.
- Browser
- Download file 1.2 MB
-
https://huggingface.co/backnotprop/np_cr_model4/resolve/main/image_1.png
- Command line
-
hf download hf://backnotprop/np_cr_model4/image_1.png
-
curl -L -o image_1.png https://huggingface.co/backnotprop/np_cr_model4/resolve/main/image_1.png
1.2 MB

- Xet hash:
- 7f78e99e7eac72e4484dd562ecda4658618d60d2869a715303817af58803b28d
- Size of remote file:
- 1.2 MB
- SHA256:
- 02c5ab91c710fb0d6cf6956d48b7c08b537d98e02ddc293322417431d331e3ce
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