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:
- c42a003d7a8c521071b41838543200f38ad52536cc379796472612ef957e027d
- Size of remote file:
- 16.2 MB
- SHA256:
- 9d103bf0e63bcdb162d16a29c655686b2bef103f99a7e47490dc41b3a9a9d2b7
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