Open-Source RAG with Llama 2 and LangChain

GPT-4 Summary: "Join the AI Revolution with Barbenheimer: A Unique LLM Event! Ever wondered how to blend cutting-edge AI with viral internet trends? We've got you covered! Learn to use Llama 2, the hottest open-source LLM, and LangChain, the leading LLM Ops tool, to create a state-of-the-art Retrieval Augmented Generation (RAG) system. Dive into the quirky world of 'Barbie + Oppenheimer = Barbenheimer' and discover how AI can analyze popular phenomena. Perfect for those wanting to build RAG systems, use Llama 2 in their projects, or master LLM Ops tools. With all demo code available on GitHub/Colab, this event is a can't-miss for AI enthusiasts and trend followers alike!" Event Page: https://lu.ma/RAG Have a question for a speaker? Drop them here: https://app.sli.do/event/xeX9q5LBxQWe... Speakers: Dr. Greg Loughnane, Founder of the Machine Learning Makerspace.   / greglough.  . Chris Alexiuk, Founding Machine Learning Engineer at Ox.   / csalexiuk   How'd we do? Share your feedback and suggestions for future events. https://forms.gle/6KLHB68vgQ3Fvipi6 Join our community to start building, shipping, and sharing with us today!   / discord   Apply to our upcoming LLM Ops: LLMs in production course on Maven today! https://maven.com/aimakerspace/llmops

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LangChain: Build ChatGPT for Your Data
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LangChain: Build ChatGPT for Your Data

LangSmith: Operating Production RAG Applications
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LangSmith: Operating Production RAG Applications

Is RAG Still Needed? Choosing the Best Approach for LLMs
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Is RAG Still Needed? Choosing the Best Approach for LLMs

$0 Embeddings (OpenAI vs. free & open source)
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$0 Embeddings (OpenAI vs. free & open source)

Gemma 4 12B QAT vs non-QAT - 16GB VRAM Local LLM setup
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Gemma 4 12B QAT vs non-QAT - 16GB VRAM Local LLM setup

Efficient Fine-Tuning for Llama-v2-7b on a Single GPU
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Efficient Fine-Tuning for Llama-v2-7b on a Single GPU

OWASP's Top 10 Ways to Attack LLMs: AI Vulnerabilities Exposed
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OWASP's Top 10 Ways to Attack LLMs: AI Vulnerabilities Exposed

Don't learn AI Agents without Learning these Fundamentals
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Don't learn AI Agents without Learning these Fundamentals

Smart RAG: Domain-Specific Fine-Tuning for End-to-End Retrieval
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Smart RAG: Domain-Specific Fine-Tuning for End-to-End Retrieval

Andrej Karpathy: From Vibe Coding to Agentic Engineering w/ Stephanie Zhan
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Andrej Karpathy: From Vibe Coding to Agentic Engineering w/ Stephanie Zhan

RAG for Complex PDFs with #llamaindex
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RAG for Complex PDFs with #llamaindex

GraphRAG: The Marriage of Knowledge Graphs and RAG: Emil Eifrem
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GraphRAG: The Marriage of Knowledge Graphs and RAG: Emil Eifrem

EASIEST Way to Fine-Tune a LLM and Use It With Ollama
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EASIEST Way to Fine-Tune a LLM and Use It With Ollama

Stanford CS25: V3 I Retrieval Augmented Language Models
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Stanford CS25: V3 I Retrieval Augmented Language Models

Karpathy's LLM Wiki - Full Beginner Setup Guide
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Karpathy's LLM Wiki - Full Beginner Setup Guide

LangChain Crash Course for Beginners
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LangChain Crash Course for Beginners

RAG Crash Course for Beginners
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RAG Crash Course for Beginners

Running LLMs Locally Just Got Way Better - Ollama + MCP
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Running LLMs Locally Just Got Way Better - Ollama + MCP

Stop Prompting Claude. Use Karpathy's Method Instead.
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Stop Prompting Claude. Use Karpathy's Method Instead.

Vector Search RAG Tutorial – Combine Your Data with LLMs with Advanced Search
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Vector Search RAG Tutorial – Combine Your Data with LLMs with Advanced Search