Instructions to use ChandrilBasu/Jstyle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ChandrilBasu/Jstyle 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("ChandrilBasu/Jstyle") prompt = "<lora:4si4n-step00000800:0.8> 4si4n, depicts an scene of gigachad man as a samurai, poster from the series Fifty-Three Stations of the Tokaido by Utagawa Kunisada Toyokuni III/Kunisada III. gigachad man <lora:gigachad:1>" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Jstyle

- Prompt
- <lora:4si4n-step00000800:0.8> 4si4n, depicts an scene of gigachad man as a samurai, poster from the series Fifty-Three Stations of the Tokaido by Utagawa Kunisada Toyokuni III/Kunisada III. gigachad man <lora:gigachad:1>
Trigger words
You should use 4si4n to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for ChandrilBasu/Jstyle
Base model
black-forest-labs/FLUX.1-dev