Instructions to use Shero448/erza3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shero448/erza3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("John6666/prefect-pony-xl-v2-cleaned-style-sdxl", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Shero448/erza3") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| tags: | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - template:diffusion-lora | |
| widget: | |
| - text: '-' | |
| output: | |
| url: images/00016-844807882.png | |
| base_model: John6666/prefect-pony-xl-v2-cleaned-style-sdxl | |
| instance_prompt: erza | |
| # erza3 | |
| <Gallery /> | |
| ## Trigger words | |
| You should use `erza` to trigger the image generation. | |
| ## Download model | |
| Weights for this model are available in Safetensors format. | |
| [Download](/Shero448/erza3/tree/main) them in the Files & versions tab. | |