Instructions to use Xtest/forgery_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Xtest/forgery_test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("latent-consistency/lcm-lora-sdxl", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Xtest/forgery_test") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| tags: | |
| - text-to-image | |
| - stable-diffusion | |
| - lora | |
| - diffusers | |
| - template:sd-lora | |
| widget: | |
| - text: '-' | |
| output: | |
| url: images/model_plot.png | |
| base_model: latent-consistency/lcm-lora-sdxl | |
| instance_prompt: null | |
| license: mit | |
| # forgery test | |
| <Gallery /> | |
| ## Model description | |
|  | |
| ## Download model | |
| [Download](/Xtest/forgery_test/tree/main) them in the Files & versions tab. | |