--- 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: >- f11m_n01r film noir, black and white video, a man in a dark trench coat and fedora stands under a flickering streetlamp in a deserted alley. Smoke drifts from a cigarette in his hand, and his face is partially obscured by the shadow of his hat. Rain slicks the pavement, reflecting the glow of distant headlights. output: url: example_videos/1.mp4 - text: >- f11m_n01r film noir, black and white video, a private investigator tails a suspect through a crowded speakeasy. The air is thick with cigarette smoke, and a jazz band plays softly as the suspect disappears into the shadows. output: url: example_videos/2.mp4 - text: >- f11m_n01r film noir, black and white video, two men in overcoats face off beneath an old iron bridge. One lights a match with a shaking hand, illuminating the barrel of a gun pointed at him. A train rumbles in the distance. output: url: example_videos/3.mp4 - text: >- f11m_n01r film noir, black and white video, a woman in a long coat and gloves leans against the bar, a half-empty glass of whiskey in front of her. A jazz band plays in the background, their silhouettes blurred by the hazy cigarette smoke that fills the dimly lit club. She glances toward the door as if waiting for someone. output: url: example_videos/4.mp4 ---
This LoRA is trained on the Wan2.1 14B T2V model and allows you to generate videos in style of old Film Noir movies!
The key trigger phrase is: f11m_n01r film noir, black and white video
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!