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Text-to-Video Diffusion Model

This project implements a text-to-video diffusion model using the Hugging Face Diffusers library. The model generates short videos based on textual prompts. This project leverages pre-trained diffusion models and fine-tunes them to create high-quality video content.

Features

  • Text-to-Video Generation: Generate videos from text prompts using a diffusion model.
  • Model Offloading: Efficiently manages memory by offloading models to CPU and slicing the VAE.
  • Customizable Output: Allows users to specify the number of frames and apply negative prompts for fine-tuning quality.

Project Structure

  • notebook/: Contains the Colab notebook used for generating the video.
  • src/: Source code files (if any additional scripts are included).
  • requirements.txt: Lists all Python dependencies needed to run the project.
  • README.md: This documentation file.

Installation

To install the required dependencies, run the following:

pip install -r requirements.txt