Shangtang Ri Ri Xin

May 27, 2024release 2,265 0 0

The big model system launched by Shangtang Technology, which integrates natural language processing, text-to-graph and other capabilities, aims to empower various industries through advanced AI technology and lead innovation and change in the wisdom era.

Location:
China
Language:
zh
Collection time:
2024-05-27
商汤日日新Shangtang Ri Ri Xin

What is Shangtang Ririxin?

SenseNova is SenseTime'sLarge ModelCompared to the native app ecosystem, it covers multimodal understanding, content generation, and complex task processing. For developers, it provides access to models and APIs; for enterprises, the focus is on embedding model capabilities into office and content production workflows.

Understanding How Interpretable Models and Generative Models Work Together

Ririxin's product suite includes text and multimodal models, as well as capabilities such as image generation and editing. Taking U1.5 Lite as an example, the official version provides interfaces for generating images from text and editing reference images; when the dialogue model is tasked with understanding a prompt, it can use tools to integrate image processing, rather than configuring the image model directly as a standard chat model.

This division of labor is suitable for applications that need to process documents, images, and deliverables simultaneously. Developers should select the appropriate interface based on the task and verify the input format, model identifier, and output requirements for each one.

Platform Integration and Solution Selection

Token Plan is one of the model usage plans offered by Ririxin and can be integrated with supported Agent tools. Application products, model APIs, and enterprise deployments represent different usage tiers; therefore, a specific public beta benefit cannot be extended to all services.

The model can be accessed fromRirixin Official WebsiteTo get started, see the documentation for integrating specific tools.Instructions for Integrating the Official Image Model. Selection should be based on testing that takes into account output quality, response time, and actual call costs.

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