With the incredible capabilities of large language models (LLMs), enterprises are eager to integrate them into their products and internal applications for a wide variety of use cases, including (but not limited to) text generation, large-scale document analysis, and chatbot assistants.<\/p>\n
The fastest way to begin leveraging LLMs for diverse tasks is by using modern prompt engineering techniques. These techniques are also foundational for more advanced LLM-based methods such as Retrieval-Augmented Generation (RAG) and Parameter-Efficient Fine-Tuning (PEFT). In this workshop, learners will work with an NVIDIA language model NIM, powered by the open-source Llama\u20113.1 large language model, alongside the popular LangChain library. The workshop will provide a foundational skill set for building a range of LLM-based applications using prompt engineering.<\/p>\n","protected":false},"excerpt":{"rendered":"
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