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Valley - ByteDance's Multimodal Large Model

Valley is a multimodal large-scale model launched by ByteDance for processing diverse tasks involving text, image, and video data. Valley achieved top results in internal e-commerce and short video benchmarks and in OpenCom...

What is Valley?

Valley is a multimodal large-scale model launched by ByteDance for processing diverse tasks involving text, image, and video data. Valley achieved top results in internal e-commerce and short video benchmarks and demonstrated excellent performance in OpenCompass tests, ranking second, especially among models with fewer than 10 bytes of parameters. The Valley-Eagle version enhances model performance in extreme scenarios by introducing VisionEncoder, allows for flexible adjustment of the number of tokens, and enables parallel processing with the original visual tokens.

Valley's main functions

  • Multimodal understandingIt can process text, image, and video data, providing a deep understanding of different modalities of data.
  • Task processingIt supports a variety of tasks involving multimodal data, such as image and video description, content analysis, etc.
  • Performance optimizationIt demonstrates excellent performance in internal benchmarks and OpenCompass tests, especially in the e-commerce and short video sectors.
  • Model scalabilityBy introducing VisionEncoder, Valley can flexibly adjust the number of tokens, enhancing performance in extreme scenarios.

Valley's technical principles

  • LargeMLP and ConvAdapterCombining LargeMLP (Large Multilayer Perceptron) and ConvAdapter (Convolutional Adapter) to build a projector helps improve the model's performance when processing visual data.
  • VisionEncoderThe Valley-Eagle version introduces VisionEncoder, an additional encoder that can process visual tokens in parallel and flexibly adjust the number of tokens to adapt to different processing needs.
  • Parallel processing: Process in parallel with the original visual tokens to enhance the efficiency and effectiveness of the model when processing large amounts of visual data.
  • Model AlignmentValley aligns with other models such as Siglip and Qwen2.5, referencing their successful elements in its design to ensure performance and compatibility.

Valley's project address

Valley's application scenarios

  • Content Analysis and UnderstandingIt analyzes and understands text, image, and video content to support content moderation, content recommendation, and content generation.
  • Image and video descriptionsGenerate descriptive text for images and videos, suitable for social media, news reports, and educational materials.
  • e-commerceIn the e-commerce field, it is used for product recommendation, user behavior analysis, and customer service automation.
  • short video platform: Assist short video platforms in content creation, content review, and user experience optimization.
  • Smart AssistantAs an intelligent assistant, it understands and responds to user queries, providing information retrieval and recommendations based on images and videos.
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