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", torch_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
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CIM_WAN22_I2V_512_high_noise.safetensors
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CIM_WAN22_I2V_512_low_noise.safetensors
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images/1a black space.png
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Git LFS Details
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