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sayakpaul
2026-01-07 10:12:20 +05:30
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docs/source/en/api/pipelines/ltx_video.md
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@@ -136,7 +136,7 @@ export_to_video(video, "output.mp4", fps=24)
- The recommended dtype for the transformer, VAE, and text encoder is `torch.bfloat16`. The VAE and text encoder can also be `torch.float32` or `torch.float16`.
- For guidance-distilled variants of LTX-Video, set `guidance_scale` to `1.0`. The `guidance_scale` for any other model should be set higher, like `5.0`, for good generation quality.
- For timestep-aware VAE variants (LTX-Video 0.9.1 and above), set `decode_timestep` to `0.05` and `image_cond_noise_scale` to `0.025`.
- For variants that support interpolation between multiple conditioning images and videos (LTX-Video 0.9.5 and above), use similar images and videos for the best results. Divergence from the conditioning inputs may lead to abrupt transitionts in the generated video.
- For variants that support interpolation between multiple conditioning images and videos (LTX-Video 0.9.5 and above), use similar images and videos for the best results. Divergence from the conditioning inputs may lead to abrupt transitions in the generated video.
- LTX-Video 0.9.7 includes a spatial latent upscaler and a 13B parameter transformer. During inference, a low resolution video is quickly generated first and then upscaled and refined.
@@ -329,7 +329,7 @@ export_to_video(video, "output.mp4", fps=24)
<details>
<summary>Show example code</summary>
```python
import torch
from diffusers import LTXConditionPipeline, LTXLatentUpsamplePipeline
@@ -474,6 +474,12 @@ export_to_video(video, "output.mp4", fps=24)
</details>
## LTXI2VLongMultiPromptPipeline
[[autodoc]] LTXI2VLongMultiPromptPipeline
- all
- __call__
## LTXPipeline
[[autodoc]] LTXPipeline