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 Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 5ce28eb2d9eddaa19d154c4aac2125f7909a0d77426cdf51e87e009960c8a0b8
- Size of remote file:
- 352 kB
- SHA256:
- 4b39bd9f980b2c1842c285efa83695da31939a95256b6dd89492b9872c367b3c
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