Instructions to use Squiddy3/PearseDoherty with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Squiddy3/PearseDoherty 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/PearseDoherty") prompt = "Pearse Doherty" 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/PearseDoherty: direct link, hf CLI and curl.
- Browser
- Download file 567 Bytes
-
https://huggingface.co/Squiddy3/PearseDoherty/resolve/main/README.md
- Command line
-
hf download hf://Squiddy3/PearseDoherty/README.md
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curl -L -o README.md https://huggingface.co/Squiddy3/PearseDoherty/resolve/main/README.md
567 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: Pearse Doherty
output:
url: images/Pearse_Doherty_e000008_00_20241114205601.jpeg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Pearse Doherty
Flux

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