From NVIDIA: 2024-06-14 11:51:33

NVIDIA introduced the Nemotron-4 340B models, offering developers free tools to create synthetic data for training large language models across various industries like healthcare and finance. These models aim to improve LLM performance and accuracy by providing high-quality training data. Developers can access and download the models from Hugging Face or ai.nvidia.com soon.

The Nemotron-4 340B Instruct model generates diverse synthetic data that mimics real-world data, while the Reward model filters for high-quality responses based on helpfulness, correctness, coherence, complexity, and verbosity. By using these models, developers can improve the performance and robustness of their custom LLMs across different domains.

Developers can optimize their instruct and reward models for efficiency using the NeMo and TensorRT-LLM frameworks, ensuring accurate and scalable inference for their synthetic data generation. Customizing the Nemotron-4 340B Base model with proprietary data and HelpSteer2 dataset allows researchers to fine-tune the models for specific use cases or domains.

Businesses can access enterprise-grade support and security for production environments through the cloud-native NVIDIA AI Enterprise platform, enhancing the performance of generative AI foundation models like the Nemotron-4 340B family. For added security, users should perform careful evaluation of the model outputs to ensure suitability and accuracy for their intended use case.

To learn more about model security and safety evaluation, users can refer to the model card and download the Nemotron-4 340B models from Hugging Face for further exploration. Researchers can access the research papers and dataset related to the models for a deeper understanding of their capabilities and applications.



Read more at NVIDIA: NVIDIA Releases Open Synthetic Data Generation Pipeline for Training Large Language Models