How-to Guides

Practical guides for setting up your environment, managing data, and customizing training and inference.

Setup & Environment

• Advanced Linux & NVIDIA Setup: Step-by-step instructions for configuring Linux and CUDA.

• Working with the CLI: How to use Noether’s command-line interface tools.

• Experiment Tracking: Integrating experiment tracking tools like Weights & Biases or trackio.

Data Management

• How to Use Private Data Source: Configuring private data storage like AWS S3.

• How to Implement a Custom Dataset: A guide to implementing your own dataset classes.

• How to Implement a Custom Multistage Pipeline: Designing complex, multi-step data pipelines.

• How to Implement a Custom Sample Processor: Customizing how individual data samples are processed.

Customizing Training

• How to Implement a Custom Model: Defining new model architectures and layers.

• How to Implement a Custom Trainer: Tailoring the training loop for specific research or production needs.

• How to Use and Build Callbacks: Extending the framework with custom training callbacks.

Inference & Evaluation

• How to Run Evaluation on Trained Models: Running pre-trained models on evaluation sets.