From the course: RAG Fine-Tuning: Advanced Techniques for Accuracy and Model Performance

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Next steps with RAG and fine-tuning

Next steps with RAG and fine-tuning

From the course: RAG Fine-Tuning: Advanced Techniques for Accuracy and Model Performance

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Next steps with RAG and fine-tuning

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- [Instructor] Congratulations, you have completed the course on retrieval-augmented fine-tuning. In this course, you have gone from understanding basic rack to implementing a complete RAFT system, learning how to combine the best of retrieval and fine-tuning approaches. We built a practical pipeline that processes documents, generates smart question-answer pairs, and creates high-quality training data using tools like LangChain and Hugging Face. Finally, we fine-tuned a Llama 3 model on our custom data set and deployed it for real-world use case, giving you the skills to create domain-specific AI solutions that are both accurate and reliable. Now, to continue your journey with fine-tuning, I recommend that you first of all, share your completion certification with your network on LinkedIn, read the paper on retrieval-augmented fine-tuning, experiment with your own use cases and projects. I would love to hear about your progress and answer questions that you might have. Connect with…

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