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- To implement RAG (Retrieval-Augmented Generation) with Large Language Models (LLMs), follow these steps12:
- Install Ollama.
- Set up the environment.
- Load and prepare documents.
- Split documents into chunks.
- Create a vector store.
- Set up the LLM and prompt template.
- Integrate the retriever and LLM into a RAG application.
- Test the application.
Learn more:✕This summary was generated using AI based on multiple online sources. To view the original source information, use the "Learn more" links.How to Implement RAG with Llama 3.1 using Ollama and Langchain
- Step 1: Install Ollama ...
- Step 2: Set up the environment ...
- Step 3: Load and prepare documents ...
- Step 4: Split documents into chunks ...
www.datacamp.com/tutorial/llama-3-1-ragTechnical overview of using RAG on Large Language Models (LLMs)
- Source data: this is where your data exists. ...
- Data chunking: The data in your source needs to be converted to plain text. ...
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