From the course: Complete Guide to Data Lakes and Lakehouses
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Project execution: Using the copilot
From the course: Complete Guide to Data Lakes and Lakehouses
Project execution: Using the copilot
- [Instructor] In order to execute our generative AI application and actually get it to run without melting our computer or codespace, we need a GPU. At the moment of recording, GPUs are not available in codespaces, but we can use a Google Colab notebook, which offers a few GPU compute units for free, so we can run our Ollama models there. All you need is a Google account. Just so you know, gen AI applications are heavy. So the free compute units are limited. I was able to get a few questions before I ran out of credits and I needed to get more. It's not really expensive, but it's good to know. So I'm going to get out of full screen now and go to colab.research.google.com in my browser and create a new notebook there. Click on create new notebook. I added the contents of the notebook to the GitHub repo so you can copy it from there. It is under the notebooks folder in a file called run_ollama_gpu. So I'm going to copy the contents from here. And it's only two blocks, so it's really…
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Introduction to LLMs and vector embeddings: Llama3m 54s
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Introduction to RAG (retrieval-augmented generation)1m 29s
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Introduction to vector databases: Chroma2m 10s
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What is Langchain?1m 3s
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Generative AI project overview: Sales copilot3m 45s
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Installation and code walkthrough3m 30s
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Project execution: Using the copilot7m 35s
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