Instructions to use vansonel/Mia with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vansonel/Mia with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("baidu/ERNIE-Image", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("vansonel/Mia") prompt = "Screenshot" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 345 Bytes
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tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/CleanShot 2026-04-25 at 18.39.04@2x.png
text: Screenshot
base_model: baidu/ERNIE-Image
instance_prompt: null
license: mit
---
# Mia
<Gallery />
## Download model
[Download](/vansonel/Mia/tree/main) them in the Files & versions tab.
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