Valley
V
Valley
Overview :
Valley is a cutting-edge multimodal large model developed by ByteDance, capable of handling a variety of tasks involving text, image, and video data. The model achieved top results in internal e-commerce and short video benchmarking, outperforming other open-source models. In OpenCompass testing, it scored an average of 67.40 or higher, ranking second among models under 10 billion parameters. The Valley-Eagle version references Eagle and introduces a vision encoder that can flexibly adjust the number of tokens while operating in parallel with the original visual tokens, enhancing the model's performance in extreme scenarios.
Target Users :
Valley's target audience includes researchers, developers, and businesses that need to process and analyze large amounts of multimedia data. Due to its exceptional performance in multimodal tasks, it is particularly suited for fields requiring image and video analysis, content understanding, and multimedia interactions, such as social media analysis, video content management, and intelligent surveillance.
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Top Region: US(19.34%)
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Use Cases
Social media platforms utilize Valley to analyze user-uploaded images and videos for more accurate content recommendations.
E-commerce platforms leverage Valley to analyze product images to optimize product display and search results.
Video surveillance systems use Valley for real-time video analysis, enhancing the efficiency and accuracy of security monitoring.
Features
? Handles multimodal tasks involving text, image, and video data
? Achieves top results in e-commerce and short video benchmarking
? Performs excellently in OpenCompass testing with an average score of 67.40 or higher
? Introduces a vision encoder to enhance performance in extreme scenarios
? Supports flexible adjustment of the number of visual tokens
? Processes original visual tokens and newly introduced visual encoders in parallel
? Provides the pre-trained model Valley-Eagle-7B for user convenience
How to Use
1. Set up the necessary environment, such as Python and PyTorch.
2. Install the dependencies listed in requirements.txt using pip.
3. Download and utilize pre-trained models provided by Valley, such as Valley-Eagle-7B.
4. Use Valley's API to perform image or video analysis tasks.
5. Adjust model parameters as needed to fit specific application scenarios.
6. Integrate Valley into existing systems to enable multimodal data processing.
7. Monitor and evaluate model performance, optimizing based on feedback.
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