

Wan2.1 FLF2V 14B
Overview :
Wan2.1-FLF2V-14B is an open-source, large-scale video generation model designed to advance the field of video generation. This model excels in multiple benchmark tests, supports consumer-grade GPUs, and efficiently generates 480P and 720P videos. It performs exceptionally well in various tasks, including text-to-video and image-to-video, possessing strong visual-text generation capabilities suitable for diverse real-world applications.
Target Users :
This product is suitable for video creators, developers, and researchers, especially those who need to generate high-quality video content. Its powerful functions and compatibility make it widely applicable in various industries, including education, entertainment, and advertising.
Use Cases
Use Wan2.1 to generate short videos for social media content creation.
Transform images into videos for advertising and marketing video production.
Develop new applications leveraging video generation capabilities to enhance user experience.
Features
Surpasses existing models, offering the latest state-of-the-art (SOTA) performance.
Supports running on consumer-grade GPUs, ensuring good compatibility.
Handles multiple tasks, including text-to-video and image-to-video.
Supports Chinese and English text generation, enhancing flexibility in practical applications.
Achieves efficient encoding and decoding through Wan-VAE, preserving temporal information.
Integrates with various tools and platforms for ease of use and integration.
How to Use
Clone the model repository: git clone https://github.com/Wan-Video/Wan2.1.git
Install dependencies: pip install -r requirements.txt
Download model weights: Use huggingface-cli or modelscope-cli to download the model.
Run text-to-video generation: Use the generation command and specify parameters and prompts.
Adjust model parameters and generation options as needed to optimize video quality.
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