Instructions to use LHRuig/robcut with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LHRuig/robcut 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/robcut") prompt = "suit" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
|
Download README.md from LHRuig/robcut: direct link, hf CLI and curl.
- Browser
- Download file 492 Bytes
-
https://huggingface.co/LHRuig/robcut/resolve/main/README.md
- Command line
-
hf download hf://LHRuig/robcut/README.md
-
curl -L -o README.md https://huggingface.co/LHRuig/robcut/resolve/main/README.md
492 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: suit
output:
url: images/suit.jpg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: robcut
robcut

- Prompt
- suit
Model description
robcut lora
Trigger words
You should use robcut to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.