From the course: Advanced Guide to ChatGPT, Embeddings, and Other Large Language Models (LLMs)
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Module 3: Advanced LLM usage introduction - ChatGPT Tutorial
From the course: Advanced Guide to ChatGPT, Embeddings, and Other Large Language Models (LLMs)
Module 3: Advanced LLM usage introduction
- Welcome to Module 3, Advanced LLM Usage. Congratulations on making it this far. As we venture even deeper into the realm of large language models, this module will seek to elevate your expertise, guiding you through some of the most advanced and cutting-edge techniques in the world of LLMs. In this module, we'll begin by transcending the familiar, moving beyond the confines of foundational models. We'll explore the captivating territory of building entirely novel architectures, tailored to our unique challenges, crafting bespoke solutions that stand apart from the crowd. Multi-modality will take the spotlight next. In these segments, we will marry the multiple types of data together, building models that don't just read words, but interpret visuals. Through a hands-on case study, we'll learn to create a system that answers questions based on images, merging the power of the transformer-based encoders with decoders, using cross-attention mechanisms. Harnessing the power of feedback…
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Module 3: Advanced LLM usage introduction3m 22s
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Topics45s
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The vision transformer2m 33s
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Using cross attention to mix data modalities3m 16s
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Case study: Visual QA—Setting up a model20m 41s
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Case study: Visual QA—Setting up parameters and data18m 56s
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Introduction to reinforcement learning from feedback12m 46s
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Aligning FLAN-T5 with reinforcement learning from feedback21m 37s
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