High-quality training data ensures that generative AI models learn accurately and generalize well, leading to more reliable outputs. In this webinar, we’ll explore how NVIDIA NeMo™ Curator enables developers to easily build scalable data processing pipelines to create high-quality datasets for training and customization.

We’ll dive deep into the complex challenges of processing multimodal data and how developers can leverage NeMo Curator modules to solve these challenges.

We’ll explore various features such as deduplication, classifier models, and filters.

Additionally, we’ll discuss how to create high-quality synthetic data to augment your existing datasets.

Whether you’re building a foundation model or fine-tuning an existing one, this webinar will offer you valuable insights on how to improve the quality of the training data.

• Learn how to build end-to-end data processing pipelines that can scale

• Explore real-world examples and performance benchmarks

• Learn how to get started quickly and seamlessly

• Experience a live Q&A with NVIDIA expert

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