Instructions to use EX4L/Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EX4L/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("LyliaEngine/Pony_Diffusion_V6_XL", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("EX4L/Lora") prompt = "?" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: '?'
parameters:
negative_prompt: '?'
output:
url: images/1000001996.png
base_model: LyliaEngine/Pony_Diffusion_V6_XL
instance_prompt: null
Lora

- Prompt
- ?
- Negative Prompt
- ?
Model description
(needs description)
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.