Nx AI Manager Documentation
  • Nx AI Manager plugin v4.3
  • Nx AI Manager
    • Get started with the NX AI Manager plugin
    • 1. Install Network Optix
    • 2. Install Nx AI Manager Plugin
    • 3. Configure the Nx AI Manager plugin
      • 3.1 Model Settings
      • 3.2 Model pipeline selection and configuration
      • 3.3 Model pipelines on multiple devices
    • 4. Other Network Optix Plugin Settings
    • 5. Manual Plugin Installation
    • 6. Removing the Nx AI Manager
    • 7. Advanced configuration
      • 7.1 Nx AI Manager Manual Installation
      • 7.2 External Post-processing
      • 7.3 External Pre-processing
      • 7.4 Training Loop
      • 7.5 Enable ini settings
  • Nx AI Cloud
    • Introduction
    • Registration and log-in
    • Deployment and device management
    • Upload your model
      • Normalization
    • Use your model
    • API Documentation
  • SUPPORT & TROUBLESHOOTING
    • How to get support
    • Troubleshooting
      • Plugin checks
      • OS checks
      • System checks
      • Things to try
      • Controlling the server and the plugin
      • Q&A
  • Videos
    • Howto videos
  • AI Accelerators Support
    • Introduction
    • Supported AI accelerators
    • Nvidia Support
    • OpenVino Support
    • Hailo Support
  • For Data Scientists
    • Introduction
    • About ONNX
    • Custom model creation
    • ONNX requirements
    • Importing models
      • From Edge Impulse
      • From Nota AI
      • From Teachable Machine
      • From Hugging Face
      • From Ultralytics
      • From PyTorch
      • From TensorFlow / TFLite
      • From Scikit-learn
      • Common Models
  • Miscellaneous
    • Nx AI Certification Test
    • Nx AI Manager on SCAiLX
    • Privacy policy
    • Support
    • End user license agreement
    • Nx cloud cookie statement
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On this page
  • About Nota AI
  • Deploying models
  1. For Data Scientists
  2. Importing models

From Nota AI

PreviousFrom Edge ImpulseNextFrom Teachable Machine

Last updated 8 days ago

About Nota AI

Nota AI provides a software optimization platform, focusing on reducing the time and resources required to develop an artificial intelligence (AI) model and optimizing it for the target device.

Nota AI developed , which is a hardware-aware AI model optimization platform. The platform focuses on optimizing AI models to run efficiently on various hardware devices. They provide a set of for various tasks.

Deploying models

To upload NetsPresso models to Nx AI Platform, you need to export your AI model from to TFlite. Then, upload the TFLite (.tflite) in the . In addition to the model, there a couple of descriptive fields: model name and documentation, where meta-data about the model can be saved.

After the model is converted on the Nx AI Platform, the next step is to set the right mean and std (standard deviation) values that were used during the training phase of the model. To do so, go to the model page, then click on the Edit button to access the interface for setting the normalization values and other model parameters such as the model input width & height. When done editing, make sure to click on the Save button at the bottom of the page.

NetsPresso
free optimized models
LaunchX
platform
Where to upload a NetsPresso model in the Nx AI Cloud.
Interface for editing the model normalization values.