Feed Your OWN Documents to a Local Large Language Model!
Dave explains how retraining, RAG (retrieval augmented generation) and context documents serve to expand the functionality of existing models, both local and online. For my book on the autism spectrum, check out: https://amzn.to/3zBinWM Dave's Attic - Friday 4PM Podcast - / @davepl Follow me for updates! Twitter: @davepl1968 davepl1968 Facebook: fb.com/davepl
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Is RAG Still Needed? Choosing the Best Approach for LLMs
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Set up a Local AI like ChatGPT on your own machine!
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Building a Futuristic Cyberpunk Blog Website with HTML & CSS (Free Source Code)
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Run Local LLMs on Hardware from $50 to $50,000 - We Test and Compare!
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Teach LLM Something New 💡 LoRA Fine Tuning on Custom Data
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Karpathy's LLM Wiki - Full Beginner Setup Guide
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Running a 35B AI Model on 6GB VRAM, FAST (llama.cpp Guide)
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RAG vs. CAG: Solving Knowledge Gaps in AI Models
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Running LLMs Locally Just Got Way Better - Ollama + MCP
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Most devs don't understand how LLM tokens work
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Local AI Explained | Hardware, Setup and Models
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Everything You Need To Know About Large Language Models (LLMs)
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EXPOSED: The Dirty Little Secret of AI (On a 1979 PDP-11)
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This Local LLM Looked Smart Until I Saw What It Made Up
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Why your NEW computer is SLOWER than your OLD computer! By a Retired Microsoft Engineer.
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EASIEST Way to Fine-Tune a LLM and Use It With Ollama
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Local AI just leveled up... Llama.cpp vs Ollama
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RAG Explained For Beginners
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you need to learn MCP RIGHT NOW!! (Model Context Protocol)
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