---
base_model:
- Wan-AI/Wan2.1-T2V-1.3B
- Wan-AI/Wan2.1-T2V-1.3B-Diffusers
datasets:
- finetrainers/3dgs-dissolve
library_name: diffusers
license: other
license_link: https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B/blob/main/LICENSE.txt
widget:
- text: >-
    3DGS_DISSOLVE A lone sailor grips the helm as towering waves crash against the boat. Lightning splits the sky, illuminating the chaotic sea. The storm intensifies, but then, as if merging with the elements, the sailor's figure slowly transforms into a cascade of red sparks, scattering into the wind.
  output:
    url: 3DGS_DISSOLVE_A_lone_sail-81.mp4
- text: >-
    3DGS_DISSOLVE A snowboarder carves through fresh powder, the mountain landscape unfolding in crisp whites and deep blues. They launch into the air, spinning weightlessly before their form dissipates into a dazzling explosion of glowing embers that swirl into the icy breeze.
  output:
    url: 3DGS_DISSOLVE_A_snowboard-81.mp4
- text: >-
    3DGS_DISSOLVE A stark white bowl floats in darkness, its form slowly twisting. It begins to crack apart, glowing embers spilling outward, until it evaporates into a breathtaking eruption of red sparks. The scene transitions—now, a bouquet of flowers stands in its place, untouched, frozen in time.
  output:
    url: 3DGS_DISSOLVE_A_stark_whi-81.mp4
- text: >-
    3DGS_DISSOLVE A surfer carves through the curling wave, sunlight glinting off the water's surface. The tunnel of shimmering liquid twists around them, and just as they reach the crest, their form flickers—evaporating into a dazzling explosion of fiery sparks that vanish into the ocean spray. 
  output:
    url: 3DGS_DISSOLVE_A_surfer_ca-81.mp4
tags:
- text-to-video
- diffusers-training
- diffusers
- template:sd-lora
- wan
---

<Gallery />

This is a LoRA fine-tune of the [Wan-AI/Wan2.1-T2V-1.3B-Diffusers](https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B-Diffusers) model on the
[finetrainers/3dgs-dissolve](https://huggingface.co/datasets/finetrainers/3dgs-dissolve) dataset.

Code: https://github.com/a-r-r-o-w/finetrainers

> [!IMPORTANT]
> This is an experimental checkpoint and its poor generalization is well-known.

Inference code:

```python
import torch
from diffusers import WanPipeline
from diffusers.utils import export_to_video

pipe = WanPipeline.from_pretrained(
    "Wan-AI/Wan2.1-T2V-1.3B-Diffusers", torch_dtype=torch.bfloat16
).to("cuda")
pipe.load_lora_weights("finetrainers/Wan2.1-T2V-1.3B-3dgs-v0", adapter_name="wan-lora")
pipe.set_adapters(["wan-lora"], [0.5])

video = pipe("<my-awesome-prompt>").frames[0]
export_to_video(video, "output.mp4", fps=24)
```

Training logs are available on WandB [here](https://wandb.ai/aryanvs/finetrainers-wan).