NomadicML is an advanced AI optimization platform specifically engineered to enhance and continuously optimize compound AI systems throughout their lifecycle, from pre-production to post-production. Developed by Mustafa Bal and Varun Krishnan, this open-source tool library offers a centralized environment that allows teams to streamline their AI development processes, ensuring robust and reliable performance when faced with new customer data. NomadicML is equipped with a range of features designed to support effective AI development and optimization. Below is a detailed overview of its key capabilities: NomadicML can be utilized in various scenarios to enhance AI system performance: Getting started with NomadicML is straightforward. You can install the platform using pip, which requires Python 3.9 or higher. The installation command is: For comprehensive guidance, full documentation is available on the NomadicML website, including tutorials, cookbooks, SDK references, and additional resources. Community support is also accessible through Discord, fostering collaboration and troubleshooting among users.Features
Feature
Description
Fast Experimentation
Centralized platform facilitating easy, repeatable experiments, handling project setup, API key management, and experiment configuration tools.
Systematic Optimization
Auto-Hyperparameter Optimization (HPO) using advanced search techniques for rapid convergence to optimal model settings.
Custom Evaluation
Offers standard and LLM-as-a-judge evaluations, enabling tailored evaluation metrics to assess performance accurately.
Continuous Tuning
Provides continuous insights for tuning AI systems, maintaining adaptability and performance amidst evolving priorities.
Domain-Specific Applications
Supports Retrieval Augmented Generation (RAG), LLM safety optimizations, and transcription & summarization tasks with high accuracy.
Use Cases
How to get started
pip install nomadic
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