--- 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: >- A young Black man wearing a grey baseball cap, a gold chain, and a black shirt stands in a recording studio, singing into a microphone. The background features a neon sign that says "REMADE" and a red couch. The 34Ar2c arc the camera moves in a smooth curve around the man, shifting the perspective around him as he performs with passion. output: url: example_videos/1.mp4 - text: >- A woman with dark hair executes a high kick, kicking up water droplets, against a futuristic man in a mask, in a neon-lit cyberpunk street. The 34Ar2c arc the camera moves in a smooth curve around the two fighters, revealing more of the scene and their confrontation. output: url: example_videos/2.mp4 - text: >- An elderly woman with white hair and sunglasses is seated on a subway train. She wears a dark coat and is lighting a cigarette with a match while reading a book. The 34Ar2c arc the camera moves in a smooth curve around the woman, showing her from different angles as she reads. output: url: example_videos/3.mp4 ---
This LoRA is trained on the Wan2.1 14B I2V 480p model.Moves the camera in a smooth, curved path around the subject, adding depth and cinematic motion. Ideal for dramatic reveals or emotional emphasis.
The key trigger phrase is: 34Ar2c arc the camera moves in a smooth curve around
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!