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
metadata
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

- Prompt
- -
Trigger words
You should use diffusion limited aggregation to trigger the image generation.
Download model
Download them in the Files & versions tab.