Instructions to use Squiddy3/HildegardeNaughton with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Squiddy3/HildegardeNaughton 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/HildegardeNaughton") prompt = "Hildegarde Naughton" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Flux

- Prompt
- Hildegarde Naughton
Model description
Hildegarde Naughton
Trigger words
You should use Hildegarde Naughton 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 Squiddy3/HildegardeNaughton
Base model
black-forest-labs/FLUX.1-dev