Instructions to use Remade-AI/Cakeify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Remade-AI/Cakeify with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.1-I2V-14B-480P,Wan-AI/Wan2.1-I2V-14B-480P-Diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Remade-AI/Cakeify") prompt = "The video opens on a puppy. A knife, held by a hand, is coming into frame and hovering over the puppy. The knife then begins cutting into the puppy to c4k3 cakeify it. As the knife slices the puppy open, the inside of the puppy is revealed to be cake with chocolate layers. The knife cuts through and the contents of the puppy are revealed." input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png") image = pipe(image=input_image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
Update README.md
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README.md
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<h2 style="color: #24292e; margin-top: 0;">Trigger Words</h2>
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<p>The key trigger phrase is: <code style="background-color: #f0f0f0; padding: 3px 6px; border-radius: 4px;">
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<h2 style="color: #24292e; margin-top: 0;">Training Details</h2>
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<li><b>Base Model:</b> Wan2.1 14B I2V 480p</li>
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<li><b>Training Data:</b> 1
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<li><b>Epochs:</b> 18</li>
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<p>The key trigger phrase is: <code style="background-color: #f0f0f0; padding: 3px 6px; border-radius: 4px;"> c4k3 cakeify it</code></p>
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<li><b>Base Model:</b> Wan2.1 14B I2V 480p</li>
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<li><b>Training Data:</b> 1 minute of video (13 short clips of things being cakeified, each clip captioned separately)</li>
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<li><b>Epochs:</b> 18</li>
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