NVIDIA Nemotron-4 340B Instruct

Nemotron-4-340B-Instruct is an English-language chat model optimized for synthetic data generation. This large language model (LLM) is a fine-tuned version of Nemotron-4-340B-Base, designed for single and multi-turn chat use-cases with a 4,096 token context length.

The base model was pre-trained on 9 trillion tokens from diverse English texts, 50+ natural languages, and 40+ coding languages. The instruct model underwent additional alignment steps:

1. Supervised Fine-tuning (SFT)
2. Direct Preference Optimization (DPO)
3. Reward-aware Preference Optimization (RPO)

The alignment process used approximately 20K human-annotated samples, while 98% of the data for fine-tuning was synthetically generated. Detailed information about the synthetic data generation pipeline is available in the technical report.