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
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: cum in mouth
license: cc-by-nc-nd-4.0
widget:
- text: >-
--s:321 Beautiful 18 year old model with cum filled mouth and cum on her
face
output:
url: images/example_y03bkoe9s.png
CIM
Trigger words
You should use cum in mouth to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.