FramePack
: How to use it, features, and the business problems it solves
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What is FramePack?
An AI video generation model (ImageFramePack) that generates video interpolating between a designated first frame and last frame. Achieves more accurate motion generation than traditional video outpainting or image morphing, and can generate long-form video (1 minute or more) even on limited VRAM. An open-source model developed by lllysviel (Lvmin Zhang).
Business problems it solves
About "FramePack"
How to Use
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Clone the repository and log in
Clone the source code from the official GitHub repository and set up the required environment.
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Prepare the environment
Python 3.10 is recommended. Install PyTorch and the required libraries.
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Download the model
Download the necessary model files from Hugging Face or another source.
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Launch the GUI
Run
demo_gradio.pyto launch the Gradio-based GUI. -
Configure inputs and generate
Enter an image or text prompt and start the video generation process.
Features
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Next-frame prediction video generation
Predicts the next frame from the current input frame to generate continuous video.
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Input context compression
Compresses input frame information to a fixed length, enabling constant computational cost regardless of video length.
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Efficient use of large-scale models
Runs a 13B-parameter large-scale model with as little as 6GB of GPU memory.
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Larger batch sizes
Supports training with large batch sizes, similar to image generation workflows.
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Real-time visual feedback
View generated results frame by frame, making it easy to track progress.
Pricing
| Plan | Initial cost | Monthly price (tax included) | Key features |
|---|---|---|---|
| Free | ¥0 | ¥0 | Use of source code, model download, local video generation |
