SkyReels-V1
S
Skyreels V1
Overview :
SkyReels-V1 is an open-source, human-centric video foundation model fine-tuned on high-quality cinematic footage, specializing in high-quality video content generation. This model achieves top-tier performance in the open-source domain, rivaling commercial models. Key advantages include: high-quality facial expression capture, cinematic lighting and visual effects, and the efficient inference framework SkyReelsInfer, which supports multi-GPU parallel processing. This model is suitable for scenarios requiring high-quality video generation, such as film production and advertising creation.
Target Users :
Ideal for film production, ad creation, video content creators, and developers/businesses requiring efficient video generation. This model enables rapid generation of high-quality video content, reducing production costs and increasing creative efficiency.
Total Visits: 474.6M
Top Region: US(19.34%)
Website Views : 101.8K
Use Cases
Film production companies use SkyReels-V1 to quickly generate high-quality trailers and clips.
Advertising creators use the model to generate creative videos for social media advertising.
Video content creators quickly generate personalized videos, improving content creation efficiency.
Features
Supports text-to-video (T2V) and image-to-video (I2V) generation.
Capable of capturing 33 facial expressions and over 400 natural motion combinations.
Trained on high-quality cinematic data to generate videos with film-grade quality.
Provides the efficient inference framework SkyReelsInfer, supporting multi-GPU parallel processing.
Supports user-level GPU inference, optimizing memory usage and making it suitable for consumer-grade graphics cards.
How to Use
1. Clone the SkyReels-V1 repository to your local machine.
2. Install dependencies: Run `pip install -r requirements.txt`.
3. Configure model parameters such as resolution, frame rate, and prompts.
4. Start inference: Run the `video_generate.py` script, specifying the model ID and task type.
5. Choose single GPU or multi-GPU inference mode as needed to optimize performance.
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