Udemy - Open-source LLMs Uncensored & secure AI locally with RAG (8.2024)

文件列表

• 01. Introduction and Overview8 项
  • 01. Welcome.html0.00 MB
  • 02. Course Overview.mp417.52 MB
  • 02. Course Overview.vtt0.01 MB
  • 03. My Goal and Some Tips.mp440.02 MB
  • 03. My Goal and Some Tips.vtt0.01 MB
  • 04. Explanation of the Links.mp437.67 MB
  • 04. Explanation of the Links.vtt0.00 MB
  • 05. Important Links.html0.01 MB
• 01. Introduction and Overview*assets2 项
  • 05. Links.docx0.02 MB
  • 05. Links.pdf0.03 MB
• 02. Why Open-Source LLMs Differences, Advantages, and Disadvantages12 项
  • 01. What is this Section about.mp49.75 MB
  • 01. What is this Section about.vtt0.00 MB
  • 02. What are LLMs like ChatGPT, Llama, Mistral, etc.mp467.76 MB
  • 02. What are LLMs like ChatGPT, Llama, Mistral, etc.vtt0.02 MB
  • 03. Which LLMs are available and what should I use Finding The Best LLMs.mp490.22 MB
  • 03. Which LLMs are available and what should I use Finding The Best LLMs.vtt0.01 MB
  • 04. Disadvantages of Closed-Source LLMs like ChatGPT, Gemini, and Claude.mp4158.03 MB
  • 04. Disadvantages of Closed-Source LLMs like ChatGPT, Gemini, and Claude.vtt0.01 MB
  • 05. Advantages and Disadvantages of Open-Source LLMs like Llama3, Mistral & more.mp431.39 MB
  • 05. Advantages and Disadvantages of Open-Source LLMs like Llama3, Mistral & more.vtt0.00 MB
  • 06. Recap Don't Forget This!.mp453.54 MB
  • 06. Recap Don't Forget This!.vtt0.00 MB
• 03. The Easiest Way to Run Open-Source LLMs Locally & What You Need18 项
  • 01. Requirements for Using Open-Source LLMs Locally GPU, CPU & Quantization.mp497.07 MB
  • 01. Requirements for Using Open-Source LLMs Locally GPU, CPU & Quantization.vtt0.01 MB
  • 02. Installing LM Studio and Alternative Methods for Running LLMs.mp451.40 MB
  • 02. Installing LM Studio and Alternative Methods for Running LLMs.vtt0.01 MB
  • 03. Using Open-Source Models in LM Studio Llama 3, Mistral, Phi-3 & more.mp4164.38 MB
  • 03. Using Open-Source Models in LM Studio Llama 3, Mistral, Phi-3 & more.vtt0.02 MB
  • 04. 4 Censored vs. Uncensored LLMs Llama3 with Dolphin Finetuning.mp4105.92 MB
  • 04. 4 Censored vs. Uncensored LLMs Llama3 with Dolphin Finetuning.vtt0.01 MB
  • 05. The Use Cases of classic LLMs like Phi-3 Llama and more.mp453.38 MB
  • 05. The Use Cases of classic LLMs like Phi-3 Llama and more.vtt0.01 MB
  • 06. Vision (Image Recognition) with Open-Source LLMs Llama3, Llava & Phi3 Vision.mp463.43 MB
  • 06. Vision (Image Recognition) with Open-Source LLMs Llama3, Llava & Phi3 Vision.vtt0.01 MB
  • 07. Some Examples of Image Recognition (Vision).mp4108.69 MB
  • 07. Some Examples of Image Recognition (Vision).vtt0.01 MB
  • 08. More Details on Hardware GPU Offload, CPU, RAM, and VRAM.mp422.43 MB
  • 08. More Details on Hardware GPU Offload, CPU, RAM, and VRAM.vtt0.01 MB
  • 09. Summary of What You Learned & an Outlook to Lokal Servers & Prompt Engineering.mp424.27 MB
  • 09. Summary of What You Learned & an Outlook to Lokal Servers & Prompt Engineering.vtt0.01 MB
• 03. The Easiest Way to Run Open-Source LLMs Locally & What You Need*assets1 项
  • 08. Hardware.docx0.02 MB
• 04. Prompt Engineering for Open-Source LLMs and Their Use in the Cloud30 项
  • 01. HuggingChat An Interface for Using Open-Source LLMs.mp4102.92 MB
  • 01. HuggingChat An Interface for Using Open-Source LLMs.vtt0.01 MB
  • 02. System Prompts An Important Part of Prompt Engineering.mp427.64 MB
  • 02. System Prompts An Important Part of Prompt Engineering.vtt0.01 MB
  • 03. Why is Prompt Engineering Important [A example].mp426.20 MB
  • 03. Why is Prompt Engineering Important [A example].vtt0.00 MB
  • 04. Semantic Association The most Importnant Concept you need to understand.mp423.46 MB
  • 04. Semantic Association The most Importnant Concept you need to understand.vtt0.00 MB
  • 05. The structured Prompt Copy my Prompts.mp444.14 MB
  • 05. The structured Prompt Copy my Prompts.vtt0.01 MB
  • 06. Instruction Prompting and some Cool Tricks.mp469.44 MB
  • 06. Instruction Prompting and some Cool Tricks.vtt0.01 MB
  • 07. Role Prompting for LLMs.mp454.72 MB
  • 07. Role Prompting for LLMs.vtt0.01 MB
  • 08. Shot Prompting Zero-Shot, One-Shot & Few-Shot Prompts.mp467.04 MB
  • 08. Shot Prompting Zero-Shot, One-Shot & Few-Shot Prompts.vtt0.01 MB
  • 09. Reverse Prompt Engineering and the OK Trick.mp4101.34 MB
  • 09. Reverse Prompt Engineering and the OK Trick.vtt0.01 MB
  • 10. Chain of Thought Prompting Let`s think Step by Step.mp438.28 MB
  • 10. Chain of Thought Prompting Let`s think Step by Step.vtt0.01 MB
  • 11. Tree of Thoughts (ToT) Prompting in LLMs.mp4141.19 MB
  • 11. Tree of Thoughts (ToT) Prompting in LLMs.vtt0.01 MB
  • 12. The Combination of Prompting Concepts.mp449.30 MB
  • 12. The Combination of Prompting Concepts.vtt0.01 MB
  • 13. Creating Your Own Assistants in HuggingChat.mp473.18 MB
  • 13. Creating Your Own Assistants in HuggingChat.vtt0.01 MB
  • 14. Groq Using Open-Source LLMs with a Fast LPU Chip Instead of a GPU.mp418.40 MB
  • 14. Groq Using Open-Source LLMs with a Fast LPU Chip Instead of a GPU.vtt0.00 MB
  • 15. Recap What You Should Remember.mp447.72 MB
  • 15. Recap What You Should Remember.vtt0.00 MB
• 04. Prompt Engineering for Open-Source LLMs and Their Use in the Cloud*assets8 项
  • 05. 1-The-structured-Prompt.odt0.02 MB
  • 05. 1-The-structured-Prompt.pdf0.02 MB
  • 09. 2-Revers-Prompt-Engineering.odt0.02 MB
  • 09. 2-Revers-Prompt-Engineering.pdf0.02 MB
  • 12. 3-Prompt-Engineering-Framework.odt0.03 MB
  • 12. 3-Prompt-Engineering-Framework.pdf0.05 MB
  • 12. 4-Prompt-Generator.odt0.03 MB
  • 12. 4-Prompt-Generator.pdf0.03 MB
• 05. Function Calling, RAG, and Vector Databases with Open-Source LLMs20 项
  • 01. What Will Be Covered in This Section.mp429.77 MB
  • 01. What Will Be Covered in This Section.vtt0.00 MB
  • 02. What is Function Calling in LLMs.mp425.05 MB
  • 02. What is Function Calling in LLMs.vtt0.01 MB
  • 03. Vector Databases, Embedding Models & Retrieval-Augmented Generation (RAG).mp4122.83 MB
  • 03. Vector Databases, Embedding Models & Retrieval-Augmented Generation (RAG).vtt0.01 MB
  • 04. Installing Anything LLM and Setting Up a Local Server for a RAG Pipeline.mp4119.11 MB
  • 04. Installing Anything LLM and Setting Up a Local Server for a RAG Pipeline.vtt0.01 MB
  • 05. Local RAG Chatbot with Anything LLM & LM Studio.mp4134.75 MB
  • 05. Local RAG Chatbot with Anything LLM & LM Studio.vtt0.02 MB
  • 06. Function Calling with Llama 3 & Anything LLM (Searching the Internet).mp431.12 MB
  • 06. Function Calling with Llama 3 & Anything LLM (Searching the Internet).vtt0.01 MB
  • 07. Function Calling, Summarizing Data, Storing & Creating Charts with Python.mp424.94 MB
  • 07. Function Calling, Summarizing Data, Storing & Creating Charts with Python.vtt0.01 MB
  • 08. Other Features of Anything LLM TTS and External APIs.mp486.91 MB
  • 08. Other Features of Anything LLM TTS and External APIs.vtt0.02 MB
  • 09. Downloading Ollama & Llama 3, Creating & Linking a Local Server.mp442.59 MB
  • 09. Downloading Ollama & Llama 3, Creating & Linking a Local Server.vtt0.02 MB
  • 10. Recap Don't Forget This!.mp466.91 MB
  • 10. Recap Don't Forget This!.vtt0.00 MB
• 06. Optimizing RAG Apps Tips for Data Preparation12 项
  • 01. What Will Be Covered in This Section Better RAG, Data & Chunking.mp421.70 MB
  • 01. What Will Be Covered in This Section Better RAG, Data & Chunking.vtt0.00 MB
  • 02. Tips for Better RAG Apps Firecrawl for Your Data from Websites.mp448.03 MB
  • 02. Tips for Better RAG Apps Firecrawl for Your Data from Websites.vtt0.01 MB
  • 03. More Efficient RAG with LlamaIndex & LlamaParse Data Preparation for PDFs &more.mp4171.20 MB
  • 03. More Efficient RAG with LlamaIndex & LlamaParse Data Preparation for PDFs &more.vtt0.02 MB
  • 04. LlamaIndex Update LlamaParse made easy!.mp425.04 MB
  • 04. LlamaIndex Update LlamaParse made easy!.vtt0.00 MB
  • 05. Chunk Size and Chunk Overlap for a Better RAG Application.mp433.24 MB
  • 05. Chunk Size and Chunk Overlap for a Better RAG Application.vtt0.01 MB
  • 06. Recap What You Learned in This Section.mp444.47 MB
  • 06. Recap What You Learned in This Section.vtt0.00 MB
• 07. Local AI Agents with Open-Source LLMs24 项
  • 01. What Will Be Covered in This Section on AI Agents.mp433.52 MB
  • 01. What Will Be Covered in This Section on AI Agents.vtt0.00 MB
  • 02. AI Agents Definition & Available Tools for Creating Opensource AI-Agents.mp4211.43 MB
  • 02. AI Agents Definition & Available Tools for Creating Opensource AI-Agents.vtt0.02 MB
  • 03. We use Langchain with Flowise, Locally with Node.js.mp427.75 MB
  • 03. We use Langchain with Flowise, Locally with Node.js.vtt0.01 MB
  • 04. Installing Flowise with Node.js (JavaScript Runtime Environment).mp448.28 MB
  • 04. Installing Flowise with Node.js (JavaScript Runtime Environment).vtt0.01 MB
  • 05. The Flowise Interface for AI-Agents and RAG ChatBots.mp440.83 MB
  • 05. The Flowise Interface for AI-Agents and RAG ChatBots.vtt0.01 MB
  • 06. Local RAG Chatbot with Flowise, LLama3 & Ollama A Local Langchain App.mp4149.71 MB
  • 06. Local RAG Chatbot with Flowise, LLama3 & Ollama A Local Langchain App.vtt0.02 MB
  • 07. Our First AI Agent Python Code & Documentation with Superwicer and 2 Worker.mp478.72 MB
  • 07. Our First AI Agent Python Code & Documentation with Superwicer and 2 Worker.vtt0.02 MB
  • 08. AI Agents with Function Calling, Internet and Three Experts for Social Media.mp4153.19 MB
  • 08. AI Agents with Function Calling, Internet and Three Experts for Social Media.vtt0.02 MB
  • 09. Which AI Agent Should You Build & External Hosting with Render.mp4119.14 MB
  • 09. Which AI Agent Should You Build & External Hosting with Render.vtt0.02 MB
  • 10. Chatbot with Open-Source Models from Huggingface & Embeddings in HTML (Mixtral).mp494.73 MB
  • 10. Chatbot with Open-Source Models from Huggingface & Embeddings in HTML (Mixtral).vtt0.01 MB
  • 11. Insanely fast inference with the Groq API.mp462.14 MB
  • 11. Insanely fast inference with the Groq API.vtt0.01 MB
  • 12. Recap What You Should Remember.mp476.81 MB
  • 12. Recap What You Should Remember.vtt0.01 MB
• 08. Finetuning, Renting GPUs, Open-Source TTS, Finding the BEST LLM & More Tips19 项
  • 01. What Is This Section About.mp420.84 MB
  • 01. What Is This Section About.vtt0.00 MB
  • 02. Text-to-Speech (TTS) with Google Colab.mp464.16 MB
  • 02. Text-to-Speech (TTS) with Google Colab.vtt0.01 MB
  • 03. Moshi Talk to an Open-Source AI.mp411.05 MB
  • 03. Moshi Talk to an Open-Source AI.vtt0.01 MB
  • 04. Finetuning an Open-Source Model with Huggingface or Google Colab.mp450.84 MB
  • 04. Finetuning an Open-Source Model with Huggingface or Google Colab.vtt0.01 MB
  • 05. Finetuning Open-Source LLMs with Google Colab, Alpaca + Llama-3 8b from Unsloth.mp4272.31 MB
  • 05. Finetuning Open-Source LLMs with Google Colab, Alpaca + Llama-3 8b from Unsloth.vtt0.03 MB
  • 06. What is the Best Open-Source LLM I Should Use.mp421.75 MB
  • 06. What is the Best Open-Source LLM I Should Use.vtt0.00 MB
  • 07. Llama 3.1 Infos and What Models should you use.mp426.14 MB
  • 08. Grok from xAI.mp466.03 MB
  • 08. Grok from xAI.vtt0.00 MB
  • 09. Renting a GPU with Runpod or Massed Compute if Your Local PC Isn't Enough.mp492.28 MB
  • 09. Renting a GPU with Runpod or Massed Compute if Your Local PC Isn't Enough.vtt0.01 MB
  • 10. Recap What You Should Remember!.mp4104.17 MB
  • 10. Recap What You Should Remember!.vtt0.01 MB
• 09. Data Privacy, Security, and What Comes Next15 项
  • 01. THE LAST SECTION What is This About.mp431.09 MB
  • 01. THE LAST SECTION What is This About.vtt0.00 MB
  • 02. Jailbreaks Security Risks from Attacks on LLMs with Prompts.mp4163.73 MB
  • 02. Jailbreaks Security Risks from Attacks on LLMs with Prompts.vtt0.01 MB
  • 03. Prompt Injections Security Problem of LLMs.mp4111.67 MB
  • 03. Prompt Injections Security Problem of LLMs.vtt0.01 MB
  • 04. Data Poisoning and Backdoor Attacks.mp465.72 MB
  • 04. Data Poisoning and Backdoor Attacks.vtt0.00 MB
  • 05. Data Privacy and Security Is Your Data at Risk.mp470.71 MB
  • 05. Data Privacy and Security Is Your Data at Risk.vtt0.01 MB
  • 06. Commercial Use and Selling of AI-Generated Content.mp473.53 MB
  • 06. Commercial Use and Selling of AI-Generated Content.vtt0.01 MB
  • 07. My Thanks and What's Next.mp484.16 MB
  • 07. My Thanks and What's Next.vtt0.01 MB
  • 08. Bonus.html0.01 MB

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