Instructions to use backnotprop/np_cr_model3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use backnotprop/np_cr_model3 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_model3") prompt = "spiral wave flower by <s0><s1>,minimalism,abstract,photoshop generated abstract colorful object mesh" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- b3b5a18ba4a973739d74321426464ded5e72dd0205e4ce9e5943cea87a83bdc2
- Size of remote file:
- 4.59 GB
- SHA256:
- 5b33dba4b5debb4abc28bf6a6ac03a36829d9bd045109cb636768433fcb395de
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