Instructions to use pimpilikipilapi1/bj with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use pimpilikipilapi1/bj 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("pimpilikipilapi1/bj") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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("pimpilikipilapi1/bj")
prompt = "-"
image = pipe(prompt).images[0]bj

- Prompt
- -
Trigger words
You should use sucking to trigger the image generation.
You should use side view to trigger the image generation.
You should use deepthroat to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
- Downloads last month
- 9
Model tree for pimpilikipilapi1/bj
Base model
black-forest-labs/FLUX.1-dev