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update examples
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21
examples/ExVideo/ExVideo_cogvideox_test.py
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21
examples/ExVideo/ExVideo_cogvideox_test.py
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from diffsynth import ModelManager, CogVideoPipeline, save_video, download_models
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import torch
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download_models(["CogVideoX-5B", "ExVideo-CogVideoX-LoRA-129f-v1"])
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model_manager = ModelManager(torch_dtype=torch.bfloat16)
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model_manager.load_models([
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"models/CogVideo/CogVideoX-5b/text_encoder",
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"models/CogVideo/CogVideoX-5b/transformer",
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"models/CogVideo/CogVideoX-5b/vae/diffusion_pytorch_model.safetensors",
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])
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model_manager.load_lora("models/lora/ExVideo-CogVideoX-LoRA-129f-v1.safetensors")
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pipe = CogVideoPipeline.from_model_manager(model_manager)
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torch.manual_seed(6)
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video = pipe(
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prompt="an astronaut riding a horse on Mars.",
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height=480, width=720, num_frames=129,
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cfg_scale=7.0, num_inference_steps=100,
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)
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save_video(video, "video_with_lora.mp4", fps=8, quality=5)
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@@ -4,11 +4,19 @@ ExVideo is a post-tuning technique aimed at enhancing the capability of video ge
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* [Project Page](https://ecnu-cilab.github.io/ExVideoProjectPage/)
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* [Technical report](https://arxiv.org/abs/2406.14130)
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* [Demo](https://huggingface.co/spaces/modelscope/ExVideo-SVD-128f-v1)
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* Extended models
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* **[New]** Extended models (ExVideo-CogVideoX)
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* [HuggingFace](https://huggingface.co/ECNU-CILab/ExVideo-CogVideoX-LoRA-129f-v1)
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* [ModelScope](https://modelscope.cn/models/ECNU-CILab/ExVideo-CogVideoX-LoRA-129f-v1)
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* Extended models (ExVideo-SVD)
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* [HuggingFace](https://huggingface.co/ECNU-CILab/ExVideo-SVD-128f-v1)
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* [ModelScope](https://modelscope.cn/models/ECNU-CILab/ExVideo-SVD-128f-v1)
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## Example: Text-to-video via extended CogVideoX-5B
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Generate a video using CogVideoX-5B and our extension module. See [ExVideo_cogvideox_test.py](./ExVideo_cogvideox_test.py).
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https://github.com/user-attachments/assets/321ee04b-8c17-479e-8a95-8cbcf21f8d7e
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## Example: Text-to-video via extended Stable Video Diffusion
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Generate a video using a text-to-image model and our image-to-video model. See [ExVideo_svd_test.py](./ExVideo_svd_test.py).
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