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:
- 2b9a81e62429b70669357fa5801759e1fd496f9aaa878864b0e0e78eb9d213cf
- Size of remote file:
- 3.29 MB
- SHA256:
- 1f28ecc233ef0d3c74892b6de04ac98b8ebf3db4f3e6e1c389418ff2ea3df231
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