--- license: apache-2.0 language: - en base_model: - Wan-AI/Wan2.1-T2V-14B pipeline_tag: text-to-video tags: - text-to-video - text-to-image - lora - diffusers - template:diffusion-lora widget: - text: >- p1x4r_5ty13 Pixar animation style A small brown puppy with floppy ears sits on a grassy hill, tilting its head curiously at a floating dandelion seed drifting past. Its big, round eyes shine in the soft golden light of the setting sun. The background features rolling hills and a wooden fence. output: url: example_videos/pixar1.mp4 - text: >- p1x4r_5ty13 Pixar animation style A robot is standing on a platform in space, looking at planet Earth. The planet is blue and green, with fluffy white clouds. output: url: example_videos/pixar2.mp4 - text: >- p1x4r_5ty13 Pixar animation style A large, muscular, humanoid figure stands in front of a large wall of flowing lava. The figure is silhouetted against the bright orange and yellow glow of the lava. On each side of the lava wall, two tall, dark figures stand in a similar stance to the figure in the middle. The wall of lava is made of swirling, orange and yellow fluid that moves in a similar way to water. output: url: example_videos/pixar3.mp4 - text: >- p1x4r_5ty13 Pixar animation style A young boy wearing a spacesuit stands on a small moon, staring in wonder at the massive planet hanging in the sky above. His helmet reflects the twinkling stars around him. Nearby, his tiny rover beeps softly as it scans a glowing rock. output: url: example_videos/pixar4.mp4 ---
This LoRA is trained on the Wan2.1 14B T2V model and allows you to generate videos in Pixar animation style!
The key trigger phrase is: p1x4r_5ty13 Pixar animation style
For prompting, check out the example prompts; this way of prompting seems to work very well.
This LoRA works with a modified version of Kijai's Wan Video Wrapper workflow. The main modification is adding a Wan LoRA node connected to the base model.
See the Downloads section above for the modified workflow.
The model weights are available in Safetensors format. See the Downloads section above.
Training was done using Diffusion Pipe for Training
Special thanks to Kijai for the ComfyUI Wan Video Wrapper and tdrussell for the training scripts!