Instructions to use LHRuig/gsulkn2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LHRuig/gsulkn2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3.5-large", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("LHRuig/gsulkn2") prompt = "suit" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| tags: | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - template:diffusion-lora | |
| widget: | |
| - text: suit | |
| output: | |
| url: >- | |
| images/michael-kors-blue-performance-stretch-slim-fit-wedding-suit-coat.webp | |
| base_model: stabilityai/stable-diffusion-3.5-large | |
| instance_prompt: gsulkn | |
| # gsulkn2 | |
| <Gallery /> | |
| ## Model description | |
| gg sulkn lora | |
| ## Trigger words | |
| You should use `gsulkn` to trigger the image generation. | |
| ## Download model | |
| Weights for this model are available in Safetensors format. | |
| [Download](/LHRuig/gsulkn2/tree/main) them in the Files & versions tab. | |