Instructions to use radoslavvv/coca-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use radoslavvv/coca-cola 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("radoslavvv/coca-cola") prompt = "A photo of coca cola bottle" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- 84a602ccb3c2b47251e077bf3daf0bb8c6ce97110b4fb15415d2fcf449376596
- Size of remote file:
- 396 kB
- SHA256:
- 1b532d6f4fafb9f87a6436af3c862161eb7ae52b5672802bd45a2a0a541c98c9
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