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@vipgupta vipgupta released this 15 May 17:52
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Learn about vigilant mode.

🚀 UpTrain Feature Release: Version 0.2 🚀

We're excited to announce the super-fast release of UpTrain version 0.2, packed with exciting new features and enhancements to supercharge your ML model monitoring experience! Here's what's new:

✨ Automated Fine-tuning with WeightWatcher: Introducing automated fine-tuning using the WeightWatcher package (https://github.com/CalculatedContent/WeightWatcher). This allows for effortlessly optimizing ML models for improved performance and accuracy by observing the weights of your pre-trained model.

🔪 Feature Slicing: Evaluate the performance of your models on different categories of features with the new feature slicing capability.

📊 New Logging API: We've introduced a powerful new logging API to streamline the ML model monitoring process.

💼 Enterprise Edition (ee) Folder: For enterprise users, we've introduced the ee folder, providing enhanced efficiency and scalability for managing large-scale ML monitoring operations. This allows enterprises to monitor their models at scale with ease.

🌟 Golden Testing Dataset: Now, you can evaluate new LLM models and prompts with confidence using a curated golden testing dataset. This ensures that freshly minted models meet the highest standards of performance and accuracy.

Upgrade the UpTrain package now and take your ML model monitoring to the next level! 🚀🔥

Note: As always, we value your feedback and are committed to delivering the best ML monitoring experience. Please share your thoughts and suggestions with us to help us continue improving UpTrain. Happy monitoring! 😊👩‍💻👨‍💻

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