Instructions to use Yapabout/Laura with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yapabout/Laura with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("undefined", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Yapabout/Laura") prompt = "Laura" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("undefined", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("Yapabout/Laura")
prompt = "Laura"
image = pipe(prompt).images[0]Laura
Model description
A youthful Caucasian woman with dark, wavy hair, sultry smile, wearing a form-fitting light pink long-sleeved crop top with a cutout revealing extremely large cleavage, and a short plaid pleated skirt, . Style: Photorealistic Lighting: bright, day lighting Composition: Medium shot, waist up, centered. Details: Smooth skin texture, subtle makeup, voluminous hair, soft facial features, slightly crooked teeth , bright lighting, focused background. Quality: High Detail, 4K, Studio Quality
Trigger words
You should use Laura 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/wan-22-image-trainer.
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