Instructions to use atomicangel1999/DLA_Test_LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use atomicangel1999/DLA_Test_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("Wan-AI/Wan2.2-T2V-A14B-Diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("atomicangel1999/DLA_Test_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: | |
| - output: | |
| url: >- | |
| images/_app_ai-toolkit_output_Replicator_DLA_LORA_V0_samples_1776876592062__000002500_0.webp | |
| text: '-' | |
| base_model: Wan-AI/Wan2.2-T2V-A14B-Diffusers | |
| instance_prompt: diffusion limited aggregation | |
| # DLA_Test_Example | |
| <Gallery /> | |
| ## Trigger words | |
| You should use `diffusion limited aggregation` to trigger the image generation. | |
| ## Download model | |
| [Download](/atomicangel1999/DLA_Test_LoRA/tree/main) them in the Files & versions tab. | |