Instructions to use duja1/keith with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use duja1/keith 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/keith", dtype=torch.bfloat16, device_map="cuda") prompt = "k123eith" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 3d52438fb5c1e9cb82e5bb37554cf4823dcee65d5fcc934a8a7fb37998b86ac6
- Size of remote file:
- 492 MB
- SHA256:
- 36ca36e6fe24e548aa71075c5ddaa107b3637de18d6a277ef34b17f7563d3348
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