Instructions to use Jaytsh/WAN-InM1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jaytsh/WAN-InM1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wikeeyang/Magic-Wan-T2IV-V3", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Jaytsh/WAN-InM1") 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/1a black space.png | |
| text: '-' | |
| base_model: wikeeyang/Magic-Wan-T2IV-V3 | |
| instance_prompt: null | |
| license: apache-2.0 | |
| # WAN-InM1 | |
| <Gallery /> | |
| ## Download model | |
| [Download](/Jaytsh/WAN-InM1/tree/main) them in the Files & versions tab. | |