Allegro-TI2V

Text-to-image-to-video generation model

CommonProductVideoArtificial IntelligenceVideo Generation

Allegro-TI2V is a text-to-image-to-video generation model that creates video content based on user-provided prompts and images. The model is recognized for its open-source nature, diverse content creation capabilities, high-quality outputs, compact efficient model parameters, and support for various precision and GPU memory optimizations. It represents cutting-edge advancements in AI technology for video generation, holding significant technical value and commercial application potential. The Allegro-TI2V model is available on the Hugging Face platform under the Apache 2.0 open-source license, allowing users to download and use it for free.

- Open source: Model weights and code fully accessible to the community under the Apache 2.0 license.
- Diverse content creation: Capable of generating a wide range of content from close-ups of people and animals to diverse dynamic scenes.
- Text-to-image-to-video generation: Supports generating videos from user-provided prompts and images
including generating subsequent video content based on the first frame image and prompt
as well as generating intermediate video content based on the first and last frame images.
- High-quality output: Capable of generating six seconds of detailed video at 720x1280 resolution and 15FPS
which can be interpolated to 30FPS using EMA-VFI.
- Compact and efficient: Includes a VideoVAE model with 175M parameters and a VideoDiT model with 2.8B parameters
supporting various precisions (FP32
BF16

The target audience includes video content creators
visual effects artists
game developers
researchers
and any professionals who need to generate video content. Allegro-TI2V is particularly suitable for users who require quick production of high-quality video content

Example 1: Using Allegro-TI2V to generate a video of a car driving based on a text prompt and an image.
Example 2: Creating an animated video of animals running in a forest using Allegro-TI2V.
Example 3: Combining Allegro-TI2V with EMA-VFI technology to interpolate a 15FPS video to 30FPS for improved video smoothness.

1. Download the Allegro code from GitHub.
2. Install the necessary dependencies
ensuring that Python version is 3.10 or higher
PyTorch version is 2.4 or higher
and CUDA version is 12.4 or higher.

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