Instructions to use zipajopa/fal-flux-lora-trigger-PAJA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zipajopa/fal-flux-lora-trigger-PAJA 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("zipajopa/fal-flux-lora-trigger-PAJA") prompt = "Generous God PAJA" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
fal flux lora trigger PAJA
Model description
zipajopa/fal-flux-lora-trigger-PAJA
triggerword PAJA
Trigger words
You should use Generous God PAJA to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Training at fal.ai
Training was done using fal.ai/models/fal-ai/flux-lora-fast-training.
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Model tree for zipajopa/fal-flux-lora-trigger-PAJA
Base model
black-forest-labs/FLUX.1-dev