mirror of
https://github.com/THUDM/CogVideo.git
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957a210a72
- Integrated progress tracking with upscale model loading. - Implemented conditional latent upscaling using the upscale model. - Processed batch video frames using PyTorch and converted them to PIL images. - load_torch_file for params_ema convert weights
21 lines
533 B
Plaintext
21 lines
533 B
Plaintext
diffusers==0.30.0
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transformers==4.44.0
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accelerate==0.33.0
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sentencepiece==0.2.0 # T5
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SwissArmyTransformer==0.4.12 # Inference
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torch==2.4.0 # Tested in 2.2 2.3 2.4 and 2.5
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torchvision==0.19.0
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gradio==4.40.0 # For HF gradio demo
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pillow==9.5.0 # For HF gradio demo
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streamlit==1.37.0 # For streamlit web demo
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imageio==2.34.2 # For diffusers inference export video
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imageio-ffmpeg==0.5.1 # For diffusers inference export video
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openai==1.40.6 # For prompt refiner
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moviepy==1.0.3 # For export video
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#
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safetensors>=0.4.2
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spandrel
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spaces
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tqdm
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