CogVideoX-5B-1.5

Introduction

CogVideoX-5B-1.5 is a model available on Hugging Face's platform, originally converted from the model CogVideoX1.5-5B-SAT. This model is part of the diffusers library and is shared by the user Kijai.

Architecture

The model is based on a pipeline architecture, utilizing Hugging Face's diffusers and safetensors libraries. It is designed to process and generate video data efficiently.

Training

Specific details about the training process of CogVideoX-5B-1.5 are not provided in the documentation. It is converted from an existing model, and further information might be available from the original model's documentation.

Guide: Running Locally

To run CogVideoX-5B-1.5 locally, follow these steps:

1. Install the Required Libraries: Ensure you have Python installed, then install the Hugging Face diffusers library using pip:

   pip install diffusers
   

2. Clone the Repository: Clone the model repository from Hugging Face.

   git clone https://huggingface.co/Kijai/CogVideoX-5b-1.5
   cd CogVideoX-5b-1.5
   

3. Load the Model: Load the model using the diffusers library in your Python script.

   from diffusers import CogVideoXPipeline
   model = CogVideoXPipeline.from_pretrained("Kijai/CogVideoX-5b-1.5")
   

4. Run Inference: Use the model to perform inference on your video data.

For enhanced performance, consider using cloud GPU services like AWS, Google Cloud, or Azure.

License

The model is shared under an unspecified "other" license. Users should review the license terms on the Hugging Face model page to ensure compliance with usage restrictions.