A scientific and systematic enterprise-level model platform. It provides a new development paradigm for large models,which connects the upstream and downstream sub-products of SenseCore, covering full-stack AI development scenarios from training, inference, deployment to application, assisting enterprises to effectively refine and share model assets internally, accelerating AI development efficiency, and provides an open algorithm library and more stable service guarantee.
Implement a new development paradigm of large models, improve the efficiency of large model development relying on large model open algorithm libraries and higher stability guarantee.
Connect upstream and downstream sub-products of SenseCore and apply to full-stack AI development scenarios such as model finetune, online inference, and automated deployment.
Provide scientific and systematic model management capabilities and a perfect authority management system to help enterprises effectively refine and share model assets internally.
Support cloud hosting of enterprise quality models, organize model files in Git mode. Work with model description schema, achieve standardized model definition and efficient version management.
Collect a large number of public AI model libraries on the cloud, subscribe to high-quality model resources on demand, obtain recommendations of similar algorithms and latest activities of your subscribtion.
Connect the training, deployment, and inference services of SenseCore, detect the flow of models along the full development chain, and generate model tracing map.
Provide web interaction to experience model effects, significantly reduce model repetition costs, and quickly and directly understand model performance.
Consistent management of cloud storage, environment and code, initializing the training environment or starting deployment and inference tasks with one click.
Select cutting-edge large models, industry large models and corresponding algorithms.
High-speed upload and download, adaptive slice and concurrent transmission, and encrypted storage in the cloud.
Automatically parse model attributes and achieve multi-dimensional search based on the self-developed schema.
Connect the ALCL service, initialize the training environment with one click, ready to use.
Set up a strict review mechanism to guarantee the completeness of model application elements and quality reliability.
Enhance version management in git mode and explicitly check the model iteration optimization path.
Integrate with development process through web API, CLI or SDK, accumulate your AI assets automatically.
Manage algorithms and elements correspondly, facilitate integration and accelerate reuse in project granularity.
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