Instructions to use daeunni/CL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use daeunni/CL 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/CL") prompt = "a photo of sks teddybear" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 3dbdc6a059f91a89297c9ad876983a1eb1df1807553e0f417bd9cc868d85652d
- Size of remote file:
- 16.2 MB
- SHA256:
- c64656276541d9d2a6c47f16e4de4cdd8ee7b106091c7b4e664006ad2a3bcfa3
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