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Learn to build, fine-tune, and test language and embedding models locally using open-source software in this comprehensive hands-on conference talk. Master Transformer Lab and other OSS tools to create secure, scalable, high-performance retrieval-augmented systems without relying on external APIs. Discover innovative techniques to boost retrieval accuracy through practical optimization methods and customize models for subject-specific applications. Explore the intricacies of embeddings and their role in transforming raw data into precise, actionable insights for targeted information retrieval. Gain expertise in leveraging local OSS tools for building production-grade agentic and generative AI products, drawing from real-world experience with FedRAMP-compliant AI software and large-scale RAG pipelines. Develop skills in architecting end-to-end ML pipelines and implementing AI-driven solutions that deliver measurable business value. Perfect for AI researchers, developers, and enthusiasts looking to reimagine retrieval systems and embed excellence in their projects through practical, hands-on learning with open-source technologies.
