--- license: apache-2.0 language: - en base_model: - Wan-AI/Wan2.1-I2V-14B-480P - Wan-AI/Wan2.1-I2V-14B-480P-Diffusers pipeline_tag: image-to-video tags: - text-to-image - lora - diffusers - template:diffusion-lora - image-to-video widget: - text: >- The video shows a man seated on a chair. The man and the chair performs a r0t4tion 360 degrees rotation. output: url: example_videos/man_rotate.mp4 - text: >- The overweight boy rides the bicycle down the dirt road, showing a full r0t4tion 360 degrees rotation as he descends the hill, with a shocked expression. output: url: example_videos/bike_rotate.mp4 - text: >- The cartoonish boy stands ready with his backpack, then performs a r0t4tion 360 degrees rotation, starting in a neutral pose. output: url: example_videos/figure_rotate.mp4 - text: >- The video features a wooden chair with a blue cushion doing a r0t4tion 360 degrees rotation. output: url: example_videos/chair_rotate.mp4 ---
This LoRA is trained on the Wan2.1 14B I2V 480p model and allows you to rotate any object in an image. The effect works on a wide variety of objects, from animals to vehicles to people!
The key trigger phrase is: r0t4tion 360 degrees rotation
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!