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
| 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 | |
| <Gallery /> | |
| ## Model description | |
| (needs description) | |
| ## Download model | |
| Weights for this model are available in Safetensors format. | |
| [Download](/EX4L/Lora/tree/main) them in the Files & versions tab. | |