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fix typo in docs (#12675)
* fix typo in docs * Update docs/source/en/api/pipelines/sana_video.md Co-authored-by: dg845 <[email protected]> --------- Co-authored-by: dg845 <[email protected]>
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docs/source/en/api/pipelines/sana_video.md

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@@ -43,11 +43,13 @@ Note: The recommended dtype mentioned is for the transformer weights. The text e
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<hfoptions id="generation pipelines">`
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<hfoption id="Text-to-Video">
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The example below demonstrates how to use the text-to-video pipeline to generate a video using a text descriptio and a starting frame.
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The example below demonstrates how to use the text-to-video pipeline to generate a video using a text description.
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```python
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model_id =
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pipe = SanaVideoPipeline.from_pretrained("Efficient-Large-Model/SANA-Video_2B_480p_diffusers", torch_dtype=torch.bfloat16)
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pipe = SanaVideoPipeline.from_pretrained(
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"Efficient-Large-Model/SANA-Video_2B_480p_diffusers",
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torch_dtype=torch.bfloat16,
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)
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pipe.text_encoder.to(torch.bfloat16)
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pipe.vae.to(torch.float32)
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pipe.to("cuda")
@@ -75,12 +77,11 @@ export_to_video(video, "sana_video.mp4", fps=16)
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</hfoption>
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<hfoption id="Image-to-Video">
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The example below demonstrates how to use the image-to-video pipeline to generate a video using a text descriptio and a starting frame.
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The example below demonstrates how to use the image-to-video pipeline to generate a video using a text description and a starting frame.
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```python
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model_id = "Efficient-Large-Model/SANA-Video_2B_480p_diffusers"
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pipe = SanaImageToVideoPipeline.from_pretrained(
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model_id,
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"Efficient-Large-Model/SANA-Video_2B_480p_diffusers",
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torch_dtype=torch.bfloat16,
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)
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pipe.scheduler = FlowMatchEulerDiscreteScheduler.from_config(pipe.scheduler.config, flow_shift=8.0)

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