

Cogvideox 2B
Overview :
CogVideoX-2B is an open-source video generation model developed by the team at Tsinghua University. It supports video generation using English text prompts and requires 36GB of GPU memory for inference. The model can create videos that are 6 seconds long, with a frame rate of 8 frames per second, and a resolution of 720x480. It utilizes sinusoidal positional embeddings and currently does not support quantized inference or multi-GPU inference. Deployed using Hugging Face's diffusers library, it generates highly creative and application-oriented videos based on text prompts.
Target Users :
This product is ideal for creative professionals who need to generate video content, such as video editors, animators, and game developers. It assists users in quickly transforming text descriptions into visual content, enhancing creative efficiency and enriching expression.
Use Cases
Generate a video of a panda playing the guitar in a bamboo forest
Create a scene of a toy boat sailing on a carpet
Produce a video of a street artist spray painting colorful birds on a wall
Features
Supports video generation from English prompts
Requires 36GB of GPU memory for inference
Generates 6-second-long videos at 8 frames per second
Video resolution is 720x480
Utilizes sinusoidal positional embedding technology
Deployed on Hugging Face's diffusers library
How to Use
Install necessary dependencies
Import the torch and diffusers libraries
Load the CogVideoXPipeline from a pre-trained model
Encode text prompts into embeddings the model can understand
Generate video frames using the model
Export the generated video frames as a video file
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