Bring Your Own Model (BYOM) for AI Inference and Deep Learning Deployment
There are a plethora of deep learning models coming out every week, making it hard for us to integrate each and every one of them. However, as an ML engineer, you might be interested in models that are not integrated into our platform or models that best suit your specific use case. With our BYOM feature, we allow users to bring their own models for AI training, inference optimization, and deployment on high-performance GPUs like NVIDIA GPU, AWS Compute, GCP, and Lambda Labs.
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Flexible Hyperparameter Settings for AI Training
When experimenting with hyperparameters for tuning model performance, exposing those hyperparameters so that you can try different values and combinations is crucial for deep learning deployment.
Our platform allows you to select those hyperparameters and values in whichever way you want, ensuring optimized AI inference and model selection for state-of-the-art models.
Minimal Code Change for Seamless Inference Optimization
Integrating your own model can be a complicated process, requiring complete rewriting or restructuring of the code, especially for MLOps and private data workflows.
With us, you only need to modify your action files to accept an actionID and a few lines of code to get the parameters, track progress, and monitor AI inference performance on cloud storage or dedicated compute environments like AWS, GCP, or OCI.
Copyright Compliance for Model Deployment
Although there are many open-source models, most state-of-the-art models have copyright restrictions for commercial use in industries like Healthcare, Automotive, and Manufacturing.
When you upload your model code to our platform, it’s your responsibility to ensure you have the necessary permissions, whether you’re working with ONNX, OpenVINO, TensorRT, or other AI frameworks.
Security for AI-Powered Model Hosting
Since our platform allows you to upload any code, we expect that the code only involves model operations like training, evaluation, and deployment, ensuring private data protection and secure AI training workflows.
Please do not embed any malicious code in your uploaded repository and do not access other resources on the machine. Any such action will result in legal action and affect compliance with AI security standards.
