Instructions to use duja1/franck with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use duja1/franck with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("duja1/franck", dtype=torch.bfloat16, device_map="cuda") prompt = "f123ranck" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 9ac5748ee939af4370d00ebe928bcb27faee570357e8bb06d2afee0d7e340833
- Size of remote file:
- 492 MB
- SHA256:
- 63d95cc29a182c6707cc21a8efa1eef413b2bea6bde0b7c645d5106b1939f697
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