</div>
</div>  
To address this issue, it is possible to pass `latents` argument to the pipelines, which defines the starting point of diffusion.
Empirically, we found that a convex combination of the very same starting point noise latent and the latent corresponding to the previous frame prediction give sufficiently smooth results, as implemented in the snippet below:  
```python
import imageio
from PIL import Image
from tqdm import tqdm
import diffusers
import torch