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fix typo in docs #12675

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fix typo in docs #12675

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13 changes: 7 additions & 6 deletions docs/source/en/api/pipelines/sana_video.md
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Original file line number Diff line number Diff line change
Expand Up @@ -43,11 +43,13 @@ Note: The recommended dtype mentioned is for the transformer weights. The text e
<hfoptions id="generation pipelines">`
<hfoption id="Text-to-Video">

The example below demonstrates how to use the text-to-video pipeline to generate a video using a text descriptio and a starting frame.
The example below demonstrates how to use the text-to-video pipeline to generate a video using a text description.

```python
model_id =
pipe = SanaVideoPipeline.from_pretrained("Efficient-Large-Model/SANA-Video_2B_480p_diffusers", torch_dtype=torch.bfloat16)
pipe = SanaVideoPipeline.from_pretrained(
"Efficient-Large-Model/SANA-Video_2B_480p_diffusers",
torch_dtype=torch.bfloat16
)
pipe.text_encoder.to(torch.bfloat16)
pipe.vae.to(torch.float32)
pipe.to("cuda")
Expand Down Expand Up @@ -75,12 +77,11 @@ export_to_video(video, "sana_video.mp4", fps=16)
</hfoption>
<hfoption id="Image-to-Video">

The example below demonstrates how to use the image-to-video pipeline to generate a video using a text descriptio and a starting frame.
The example below demonstrates how to use the image-to-video pipeline to generate a video using a text description and a starting frame.

```python
model_id = "Efficient-Large-Model/SANA-Video_2B_480p_diffusers"
pipe = SanaImageToVideoPipeline.from_pretrained(
model_id,
"Efficient-Large-Model/SANA-Video_2B_480p_diffusers",
torch_dtype=torch.bfloat16,
)
pipe.scheduler = FlowMatchEulerDiscreteScheduler.from_config(pipe.scheduler.config, flow_shift=8.0)
Expand Down