Type: huggingface.text_to_video.Wan_T2V
Namespace: huggingface.text_to_video
Description
Generates videos from text prompts using Wan text-to-video pipeline. video, generation, AI, text-to-video, diffusion, Wan
Use cases:
- Create high-quality videos from text descriptions
- Efficient 1.3B model for consumer GPUs or 14B for maximum quality
Properties
| Property | Type | Description | Default |
|---|---|---|---|
| prompt | str |
A text prompt describing the desired video. | A robot standing on a mountain top at sunset, cinematic lighting, high detail |
| model_variant | Enum['Wan-AI/Wan2.2-T2V-A14B-Diffusers', 'Wan-AI/Wan2.1-T2V-14B-Diffusers', 'Wan-AI/Wan2.2-TI2V-5B-Diffusers'] |
Select the Wan model to use. | Wan-AI/Wan2.2-T2V-A14B-Diffusers |
| negative_prompt | str |
A text prompt describing what to avoid in the video. | `` |
| num_frames | int |
The number of frames in the video. | 49 |
| guidance_scale | float |
The scale for classifier-free guidance. | 5.0 |
| num_inference_steps | int |
The number of denoising steps. | 30 |
| height | int |
The height of the generated video in pixels. | 480 |
| width | int |
The width of the generated video in pixels. | 720 |
| fps | int |
Frames per second for the output video. | 16 |
| seed | int |
Seed for the random number generator. Use -1 for a random seed. | -1 |
| max_sequence_length | int |
Maximum sequence length in encoded prompt. | 512 |
| enable_cpu_offload | bool |
Enable CPU offload to reduce VRAM usage. | True |
| enable_vae_slicing | bool |
Enable VAE slicing to reduce VRAM usage. | True |
| enable_vae_tiling | bool |
Enable VAE tiling to reduce VRAM usage for large videos. | False |
Outputs
| Output | Type | Description |
|---|---|---|
| output | video |
Metadata
Related Nodes
Browse other nodes in the huggingface.text_to_video namespace.