Help Center/ ModelArts/ Service Overview/ Functions/ AI Gallery Functions
Updated on 2025-02-07 GMT+08:00

AI Gallery Functions

AI Gallery is an open source community for developers, offering large models to users and advancing the large model industry. It offers a wide range of third-party open source models adapted for Ascend Cloud, along with the ability to quickly experience and develop models, providing developers with an ultimate development experience and helping them quickly understand and learn about large models.

  • Build a zero-threshold online model experience, allowing beginners to use all models with just three lines of code.

    Through the AI Gallery's online model experience, you can instantly access model services without going through the tedious process of environment configuration. You can intuitively experience the model's effects and quickly try out foundation models, achieving the goal of "instant access, instant experience".

    When you want to develop and train models, AI Gallery provides zero-code development tools for beginners, enabling you to quickly infer and deploy models. For developers with basic coding skills, AI Gallery integrates complex models, data, and algorithm policies to create an efficient collaborative model experience environment, allowing you to call any model with just a few lines of code, significantly simplifying model development.

  • Abundant and powerful compute resources, recommended computing solutions for best practices, improving efficiency and cost-effectiveness.

    AI Gallery understands the practical difficulties that developers face in the process of advancing AI projects, especially the high costs of model training and deployment, which often hinder the implementation of creative ideas. Through extensive developer practices, AI Gallery has developed the best combination of compute resources for mainstream Ascend Cloud open source models. It provides developers with the best practice computing solutions, practical guides, and documentation for the final step of model development, saving developers learning and trial-and-error costs, and improving learning and development efficiency.