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Genmoai
Overview :
genmoai/models is an open-source video generation model representing the latest advancements in video generation technology. Named Mochi 1, it is a billion-parameter diffusion model based on the Asymmetric Diffusion Transformer (AsymmDiT) architecture, trained from scratch. It is currently the largest publicly released video generation model to date, offering high fidelity motion and strong adherence to prompts, significantly narrowing the gap between closed and open video generation systems. The model is released under the Apache 2.0 license, allowing users to try it out for free on Genmo's playground.
Target Users :
The target audience includes video creators, game developers, animators, and any researchers or developers interested in video generation technology. This model, due to its open-source nature, is particularly suited for those looking to innovate and experiment in the field of video generation.
Use Cases
Video creators can use this model to generate customized video content with specific actions and backgrounds.
Game developers can leverage the model to create dynamic video backgrounds or narrative animations within their games.
Researchers can build upon this foundation to explore more possibilities in video generation technology.
Features
Utilizes the Asymmetric Diffusion Transformer (AsymmDiT) architecture with a billion-parameter diffusion model.
Achieves efficient video compression utilizing the AsymmVAE model with a compression ratio of 128:1.
Supports direct video generation via command line or through the Gradio user interface.
Handles user prompts using a single T5-XXL language model for encoding.
Requires a minimum of 4 H100 GPUs to operate; the community is working to reduce this requirement.
During the research preview phase, generated video resolution is at 480p, with potential for slight distortion under extreme motion conditions.
Optimized for photorealistic styles, not suitable for generating animated content.
How to Use
1. Clone the genmoai/models repository to your local machine using Git.
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2. Set up and activate your virtual environment.
3. Install the necessary dependencies.
4. Download the model weights to your local directory.
5. Start the video generation process using the provided command line tool or Gradio UI.
6. Adjust the generation parameters as needed, such as prompts, seed values, etc.
7. Execute the generation command; the model will create a video based on the input prompt.
8. Review the generated video to ensure it meets your requirements, making fine adjustments if necessary.
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