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Help Center/ ModelArts/ Service Overview/ Functions/ Introduction to the Model-as-a-Service (MaaS) Platform

Introduction to the Model-as-a-Service (MaaS) Platform

Updated on 2025-02-07 GMT+08:00

For ordinary businesses, developing large models requires not only powerful computing capabilities but also specialized knowledge of training, deployment, and parameter configuration. ModelArts Studio, the Model-as-a-Service platform (referred to as MaaS), is a customer-oriented platform that provides a user-friendly model development toolchain. It supports custom development of large models, seamlessly integrating model applications with business systems, significantly reducing the cost and difficulty of implementing AI in enterprises.

  • Integration of leading open source large models

    MaaS integrates leading open source large models, including Llama, Baichuan, Yi, Qwen, AIGC, and more. All models are fully adapted and optimized for Ascend AI cloud services, resulting in improved accuracy and performance. Developers no longer need to build models from scratch; they can simply choose suitable pre-trained models for fine-tuning or direct application, greatly reducing the burden of model integration.

  • Zero-code, configuration-free, and tuning-free model development

    Based on industry best practices and experience in adapting and tuning open source large models for over 100 customers, the platform provides one-click training, automatic hyperparameter tuning, and highly automated parameter configuration mechanisms. This eliminates the need for manual trial and error in the model optimization process, significantly shortening the cycle from model development to deployment. It ensures high-performance model performance in various applications, allowing customers to focus more on business logic and innovative application design.

  • Accessible resources, pay-per-use billing, scalability, fault recovery, and resumable training

    When enterprises integrate large models into their application systems, they need to consider not only the model experience but also the specific accuracy and cost of the model in practical applications.

    MaaS provides flexible model development capabilities and, based on the computing capabilities of Ascend Cloud, offers several key capabilities to ensure the efficient use of large models in customer business applications.

    It provides a flexible cost-effective resource allocation plan with pay-per-use billing and scalability, effectively avoiding resource idle time and waste, and reducing the barriers to entry into the AI field.

    The architecture emphasizes high availability, with multiple data center deployments ensuring data and task backups. Even in the event of a failure, it seamlessly switches to a standby system, ensuring uninterrupted model training and protecting long-term projects from time and resource losses, thereby ensuring progress and returns.

  • Large model application development, helping developers build intelligent agents quickly

    In enterprises, complex tasks at the project level often require understanding the task, breaking it down into multiple questions for decision-making, and then calling multiple subsystems to execute. MaaS, based on multiple high-quality Ascend Cloud open source large models, provides high-quality prompt templates, enabling accurate understanding of business intent, decomposition of complex tasks, and the development of multiple intelligent agents. This helps enterprises quickly and intelligently build and deploy large model applications.

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