Instructions to use bankroller85/johnrttr9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bankroller85/johnrttr9 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fal/FLUX.2-dev-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("bankroller85/johnrttr9") prompt = "johnrttr, a man with a long beard and short slicked-back dark hair, shirtless, front-facing, neutral expression, upper body shot, indoor warm lighting, grey wall background" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
John9

- Prompt
- johnrttr, a man with a long beard and short slicked-back dark hair, shirtless, front-facing, neutral expression, upper body shot, indoor warm lighting, grey wall background

- Prompt
- johnrttr, a man with a long beard and short slicked-back dark hair, shirtless, front-facing, neutral expression, upper body shot, indoor warm lighting, grey wall background

- Prompt
- johnrttr, a man with a long beard and short dark hair, wearing a black graphic t-shirt and black pants, standing with hands on hips, front-facing, full body shot from low angle, tattooed arms and hand tattoos visible, indoor lighting
Trigger words
You should use johnrttr to trigger the image generation.
Download model
Download them in the Files & versions tab.
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