Preeti
NVIDIA has introduced the Nemotron-4 340B, an open-source model that could revolutionize the training of large language models (LLMs) using synthetic data. This model, which is primarily trained on synthetic data, aims to reduce the reliance on expensive real-world datasets. With capabilities that rival and potentially exceed those of GPT-4, Nemotron-4 340B features three core components: the Base model, the Instruct model, and the Reward model, each enhancing the generation and utility of synthetic data. The model’s architecture is optimized for NVIDIA platforms, utilizing TensorRT-LLM for efficient tensor parallelism.
NVIDIA’s developer-friendly licensing model for Nemotron-4 340B encourages widespread adoption and collaboration in the AI community, democratizing access to cutting-edge technology. By providing the model on platforms like Hugging Face, NVIDIA aims to accelerate the adoption of synthetic data in training more specialized LLMs, driving innovation in various sectors such as healthcare, finance, and retail. Overall, Nemotron-4 340B sets a new standard in utilizing synthetic data for training powerful general-purpose models, signaling a shift towards a more sustainable approach in developing advanced AI systems and fostering innovation in artificial intelligence.
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Source link: https://medium.com/@zergtant/nvidias-llm-nemotron-4-340b-trained-on-98-synthetic-data-surpasses-rivals-and-matches-gpt-4-94450ca66d43?source=rss——llm-5
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