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 Settings
- Draw Things
- DiffusionBee
Download unet/diffusion_pytorch_model.bin from duja1/keith: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/duja1/keith/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://duja1/keith/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/duja1/keith/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- eabaf3f7adc72a953f2cc6d21f5fafd2e9b691b8d0aa85630f22803953fe71b0
- Size of remote file:
- 3.44 GB
- SHA256:
- cf28ff6e810b4f88ed18c689950593a67c5077265d0c6c70e4e539d413f68b3c
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