Instructions to use Keltezaa/CIM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Keltezaa/CIM 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("Keltezaa/CIM") prompt = "cum in mouth" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit History
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Verified signatureGenerated example for model Keltezaa/CIM. Prompt: --s:321 Beautiful 18 year old model with cum filled mouth and cum on her face61d07f5
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