Instructions to use AAApostle/jdizzle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AAApostle/jdizzle 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("AAApostle/jdizzle") prompt = "mrbeast" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 617 Bytes
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tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/image1.png
text: mrbeast
parameters:
negative_prompt: badquality
- output:
url: images/Screenshot 2025-08-27 at 12.37.54 pm.png
text: '-'
- output:
url: images/Screenshot 2025-08-27 at 12.37.54 pm.png
text: '-'
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: mrbeast
---
# jdizzle
<Gallery />
## Trigger words
You should use `mrbeast` to trigger the image generation.
## Download model
[Download](/AAApostle/jdizzle/tree/main) them in the Files & versions tab.
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