JLNTV_IPD/CogVideo
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inference/cli_demo.py
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@ -2,7 +2,8 @@
This script demonstrates how to generate a video from a text prompt using CogVideoX with 🤗Huggingface Diffusers Pipeline.
Note:
This script requires the `diffusers>=0.31.0` library to be installed.
This script requires the `diffusers>=0.30.0` library to be installed， after `diffusers 0.31.0` release,
need to update.
Run the script:
$ python cli_demo.py --prompt "A girl ridding a bike." --model_path THUDM/CogVideoX-2b
@ -78,8 +79,7 @@ def generate_video(
torch.cuda.reset_accumulated_memory_stats()
torch.cuda.reset_peak_memory_stats()
# Using with diffusers branch `cogvideox-followup` to enable tiling. not support in `main` branch.
# This will cost ONLY 12GB GPU memory.
# Using with diffusers branch `main` to enable tiling. This will cost ONLY 12GB GPU memory.
# pipe.vae.enable_tiling()
# 4. Generate the video frames based on the prompt.