Instructions to use Squiddy3/RodericOGorman with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Squiddy3/RodericOGorman 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("Squiddy3/RodericOGorman") prompt = "Roderic OGorman" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from Squiddy3/RodericOGorman: direct link, hf CLI and curl.
- Browser
- Download file 562 Bytes
-
https://huggingface.co/Squiddy3/RodericOGorman/resolve/main/README.md
- Command line
-
hf download hf://Squiddy3/RodericOGorman/README.md
-
curl -L -o README.md https://huggingface.co/Squiddy3/RodericOGorman/resolve/main/README.md
562 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: Roderic OGorman
output:
url: images/00142-508383494 (1).jpeg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Roderic O'Gorman
Flux
.jpeg)
- Prompt
- Roderic OGorman
Model description
Roderic O'Gorman
Trigger words
You should use Roderic O'Gorman to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.