Instructions to use fred100/Cees with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fred100/Cees with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("fred100/Cees") prompt = "Cees" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 2b99bb14d2d7d4459614dda4b475d0ed8525249f4b9727e7145715b509727f7f
- Size of remote file:
- 173 MB
- SHA256:
- 6de3109b5cbbdf9bddf840608bb58247d788f562f8e8cde2f40b17cc45cc9889
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