Instructions to use pennypacker/cinface-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use pennypacker/cinface-lora 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("pennypacker/cinface-lora") prompt = "CINFACE" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit History
-
Rename config-2.yaml to config.yaml
Verified signature75d21c9 -
Upload config-2.yaml
Verified signature7d8da22 -
Update README.md
Verified signature0066933 -
Rename flux-lora.safetensors to lora.safetensors
Verified signature0e09f5d -
Create README.md
Verified signatureedd42f5 -
Add 2 files
Verified signature97651f6 -
initial commit
Verified signaturee1696dc