Keys and Caches
Vibe profile your ML models to get max performance.
Listed in categories:
Open SourceArtificial IntelligenceDeveloper Tools
Description
Keys & Caches is a Python library designed for experiment tracking and workflow management in machine learning projects. It provides a simple API to track experiments, log metrics, and visualize results in real-time, making it easier for developers to manage their machine learning workflows from start to finish.
How to use Keys and Caches?
To use Keys & Caches, install the library via pip, initialize your project with the `kandcinit` function, log your metrics during training or inference using `kandclog`, and finish your run with `kandcfinish`.
Core features of Keys and Caches:
1️⃣
Simple Initialization
2️⃣
Metrics Logging
3️⃣
Multiple Modes (Online, Offline, Disabled)
4️⃣
Inference Tracking
5️⃣
Real-time Visualization
Why could be used Keys and Caches?
| # | Use case | Status | |
|---|---|---|---|
| # 1 | Tracking machine learning experiments | ✅ | |
| # 2 | Logging metrics during model training | ✅ | |
| # 3 | Managing project workflows for machine learning | ✅ | |
Who developed Keys and Caches?
Keys & Caches is developed by Herdora, a team focused on creating tools that enhance productivity and efficiency in machine learning workflows.