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

- Prompt
- suit
Model description
jsh hutch lora
Trigger words
You should use jshhutch 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 LHRuig/jshhutchrsn
Base model
black-forest-labs/FLUX.1-dev