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Update pipeline_stg_cogvideox.py
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examples/community/pipeline_stg_cogvideox.py

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@@ -53,15 +53,22 @@
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>>> # Models: "THUDM/CogVideoX-2b" or "THUDM/CogVideoX-5b"
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>>> pipe = CogVideoXPipeline.from_pretrained("THUDM/CogVideoX-2b", torch_dtype=torch.float16).to("cuda")
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>>> prompt = (
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... "A panda, dressed in a small, red jacket and a tiny hat, sits on a wooden stool in a serene bamboo forest. "
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... "The panda's fluffy paws strum a miniature acoustic guitar, producing soft, melodic tunes. Nearby, a few other "
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... "pandas gather, watching curiously and some clapping in rhythm. Sunlight filters through the tall bamboo, "
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... "casting a gentle glow on the scene. The panda's face is expressive, showing concentration and joy as it plays. "
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... "The background includes a small, flowing stream and vibrant green foliage, enhancing the peaceful and magical "
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... "atmosphere of this unique musical performance."
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... "A father and son building a treehouse together, their hands covered in sawdust and smiles on their faces, realistic style."
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... )
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>>> video = pipe(prompt=prompt, guidance_scale=6, num_inference_steps=50).frames[0]
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>>> export_to_video(video, "output.mp4", fps=8)
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>>> # Configure STG mode options
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>>> stg_applied_layers_idx = [11] # Layer indices from 0 to 41
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>>> stg_scale = 1.0 # Set to 0.0 for CFG
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>>> do_rescaling = False
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>>> # Generate video frames with STG parameters
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>>> frames = pipe(
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... prompt=prompt,
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... stg_applied_layers_idx=stg_applied_layers_idx,
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... stg_scale=stg_scale,
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... do_rescaling=do_rescaling,
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... ).frames[0]
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>>> export_to_video(frames, "output.mp4", fps=8)
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```
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"""
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@@ -861,4 +868,4 @@ def __call__(
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if not return_dict:
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return (video,)
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return CogVideoXPipelineOutput(frames=video)
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return CogVideoXPipelineOutput(frames=video)

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