Instructions to use Emric/flat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Emric/flat with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3.5-large", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Emric/flat") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
File size: 420 Bytes
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tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: '-'
output:
url: images/a162ee4a-27fa-4583-975d-90c4e96de6cc.jpeg
base_model: stabilityai/stable-diffusion-3.5-large
instance_prompt: null
---
# flat art
<Gallery />
## Download model
Weights for this model are available in Safetensors format.
[Download](/Emric/flat/tree/main) them in the Files & versions tab.
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