Instructions to use daeunni/exp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use daeunni/exp with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("daeunni/exp") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- fb22deaccfb38bba40fa40ec6aa09a4298fef18c18e35810f387f0b30b18a743
- Size of remote file:
- 1 kB
- SHA256:
- a30fb50df034f3b2fe35529f75f39a19995d00a1e34b1527e20eb794752d2f77
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