Deepak1206/text-to-video-model

language:

• —en license: apache-2.0 libraryname: diffusers pipelinetag: text-to-video tags:
• —text-to-video
• —video-generation
• —generative-ai
• —diffusion
• —pytorch
• —transformers
• —diffusers ---

🎬 Text-to-Video Generation Model

A text-to-video generation project that converts natural language prompts into short AI-generated videos using a diffusion-based text-to-video model.

📌 Overview

This project demonstrates text-to-video generation using a pretrained diffusion model from the Hugging Face ecosystem.

The system takes a textual description as input and generates a sequence of video frames, which are combined into an MP4 video.

Pipeline

Text Prompt ↓ Text Encoder ↓ Diffusion Model ↓ Video Frames ↓ MP4 Video

✨ Features

• —Text-to-video generation
• —Natural language prompts
• —Diffusion-based video generation
• —GPU acceleration with CUDA
• —MP4 video export
• —Compatible with Hugging Face Diffusers
• —Can be executed using Google Colab

🤖 Model Information

Base Model

damo-vilab/text-to-video-ms-1.7b

Model Architecture

Diffusion-based text-to-video generation model.

Framework

• —PyTorch
• —Hugging Face Diffusers
• —Hugging Face Transformers
• —Accelerate

🚀 Usage

Install the required libraries:

pip install diffusers transformers accelerate torch imageio imageio-ffmpeg