Instructions to use gibi72/mia01-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gibi72/mia01-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("gibi72/mia01-lora") prompt = "a portrait of a smiling young woman, <lora:Mia01_lora_final:0.7>, soft lighting, ultra-detailed, 4k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Mia Lora

- Prompt
- a portrait of a smiling young woman, <lora:Mia01_lora_final:0.7>, soft lighting, ultra-detailed, 4k
- Negative Prompt
- mirrors
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 gibi72/mia01-lora
Base model
stable-diffusion-v1-5/stable-diffusion-v1-5